Septimiu Salcudean

Professor

Relevant Degree Programs

 

Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - May 2019)
Towards photoacoustic tomography for robot-assisted prostate imaging (2019)

During prostate surgeries, there are critical structures around the prostate that should be preserved. Therefore, an additional intra-operative prostate cancer (PCa) imaging method is needed to help the surgeon localize the cancer. Photoacoustic (PA) imaging as an emerging imaging modality shows great potential to detect cancerous tissue. In this thesis, we focus on intra-operative PA imaging of the prostate using the da Vinci robotic system.Towards this objective, we developed a PA reconstruction technique that works in the presence of the challenges of the linear transducers. These challenges include the directivity effect of the transducer and limited-view PA imaging that cause the rank deficiency of the reconstruction system. Therefore, a sparse representation of the PA absorber distribution using the Discrete Cosine Transform was proposed. This sparse representation helps improve the numerical conditioning of the system of equations and reduces the computation time of the approach.In addition, we evaluated the feasible scanning configurations for intra-operative PA tomography (PAT) of the prostate. There are two ultrasound transducers that can be used in prostate PAT: a transrectal ultrasound (TRUS) transducer located posterior to the prostate, and a pick-up ultrasound transducer carried by the da Vinci robotic system and located anterior to the prostate. We proposed a PAT acquisition system that includes a da Vinci system controlled by the da Vinci Research Kit. The configurations using the pick-up and the TRUS transducers to perform intra-operative prostate PAT were investigated.Finally, we developed intra-operative prostate PA imaging using the da Vinci robotic system and a pick-up ultrasound transducer. We proposed a new approach in which the da Vinci robot is programmed to acquire trajectories in a shared control configuration with virtual fixtures; the pick-up transducer is manually controlled but virtual fixtures keep it parallel to a single tomography axis, and keep its translation fixed to a single plane normal to this axis. The surgeon controls the transducer motion on the tissue along this virtual fixture. This thesis confirms that intra-operative da Vinci robot-assisted PA imaging with a pick-up transducer is feasible.

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Ultrasound elastography for intra-operative use and renal tissue imaging (2017)

The kidney is a vital organ within the human body and improvements in the ability to characterize the kidney tissue can create benefits for patients with kidney tumors and for kidney transplant recipients. Often, changes in tissue health or development of cancer are manifested in changes in tissue structure that affect tissue elastic properties. For example, the cancerous tissue of renal cell carcinoma is stiffer than healthy kidney tissue, and the development of fibrosis, which impairs kidney function, also causes the tissue to become stiffer over time. These changes can be imaged with ultrasound elastography, a technique for quantitatively assessing tissue elasticity. If proven effective, elastography tissue characterization can replace biopsy.The ultrasound elastography method used in this thesis, called Shear Wave Absolute Vibro-Elastography, or SWAVE, measures the wavelength of induced steady-state multi-frequency mechanical shear waves to calculate tissue elasticity. SWAVE can employ standard ultrasound transducers that image the kidney though the skin above the organ, or custom miniaturized transducers that are placed directly on the surface of the organ during surgery. The accuracy of SWAVE is vastly improved by the use of 3D ultrasound data. We propose and evaluate 3D SWAVE imaging based on the use of a tracked intra-operative ultrasound transducer designed for use with the da Vinci Robot. Different tracking methods are evaluated for future intra-operative use. Elasticity images of tissue phantoms are obtained using interpolated 3D tissue displacement data acquired with the da Vinci robot and the intra-operative transducer. The use of tracked ultrasound transducer opens the way for introducing registered preoperative imaging, including elastography, to improve surgical guidance. Different methods of characterizing kidney tissue using SWAVE imaging are examined. The elastic and viscous properties are estimated kidney tissue ex-vivo. The effect of arterial pressure on the measured kidney elasticity is characterized. It was found that increasing input pressure increases the measured elasticity. Finally, ultrasound and ultrasound elastography are applied to kidney transplant recipients in-vivo to assess the level of fibrosis development. A preliminary study indicates that it is possible to transmit shear waves into the transplanted kidney and measure the elastic properties of the kidney tissue.

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Three dimensional ultrasound elasticity imaging (2016)

Changes in tissue elasticity are correlated with certain pathological changes, such as localized stiffening of malignant tumours or diffuse stiffening of liver fibrosis or placenta dysfunction. Elastography is a field of medical imaging that characterizes the mechanical properties of tissue, such as elasticity and viscosity. The elastography process involves deforming the tissue, measuring the tissue motion using an imaging technique such as ultrasound or magnetic resonance imaging (MRI), and solving the equations of motion. Ultrasound is well suited for elastography, however, it presents challenges such as anisotropic measurement accuracy and providing two dimensional (2D) measurements rather than three dimensional (3D). This thesis focuses on overcoming some of these limitations by improving upon methods of imaging absolute elasticity using 3D ultrasound. In this thesis, techniques are developed for 3D ultrasound acquired from transducers fitted with a motor to sweep the image plane, however many of the techniques can be applied to other forms of 3D acquisition such as matrix arrays. First, a flexible framework for 3D ultrasound elastography system is developed. The system allows for comparison and in depth analysis of errors in current state of the art 3D ultrasound shear wave absolute vibro-elastography (SWAVE). The SWAVE system is then used to measure the viscoelastic properties of placentas, which could be clinically valuable in diagnosing preeclampsia and fetal growth restriction. A novel 3D ultrasound calibration technique is developed which estimates the transducer motor parameters for accurate determination of location and orientation of every data sample, as well as for enabling position tracking of a 3D ultrasound transducer so multiple volumes can be combined. Another calibration technique using assumed motor parameters is developed, and an improvement to an existing N-wire method is presented. The SWAVE research system is extended to measure shear wave motion vectors with a new acquisition scheme to create synchronous volumes of ultrasound data. Regularization based on tissue incompressibility is used to reduce noise in the motion measurements. Lastly, multiple ultrasound volumes from different angles are combined for measurement of the full motion vector, and demonstrating accurate reconstructions of elasticity are feasible using the techniques developed in this thesis.

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Image and haptic guidance for robot-assisted laparoscopic surgery (2015)

Surgical removal of the prostate gland using the da Vinci surgical robot is the state of the art treatment option for organ confined prostate cancer. The da Vinci system provides excellent 3D visualization of the surgical site and improved dexterity, but it lacks haptic force feedback and subsurface tissue visualization. The overall objective of the work done in this thesis is to augment the existing visualization tools of the da Vinci with ones that can identify the prostate boundary, critical structures, and cancerous tissue so that prostate resection can be carried out with minimal damage to the adjacent criticalstructures, and therefore, with minimal complications. Towards this objective we designed and implemented a real-time image guidance system based on a robotic transrectal ultrasound (R-TRUS) platform that works in tandem with the da Vinci surgical system and tracks its surgical instruments. In addition to ultrasound as an intrinsic imaging modality, the system was first used to bring pre-operative magnetic resonance imaging (MRI) to the operating room by registering the pre-operative MRI to the intraoperative ultrasound and displaying the MRI image at the correct physical location based on the real-time ultrasound image. Second, a method of using the R-TRUS system for tissue palpation is proposed by expanding it to be used in conjunction with a real-time strain imaging technique. Third, another system based on the R-TRUS is described for detecting dominant prostate tumors, based on a combination of features extracted from a novelmulti-parametric quantitative ultrasound elastography technique. We tested our systems in an animal study followed by human patient studies involving n = 49 patients undergoing da Vinci prostatectomy. The clinical studies were conducted to evaluate the feasibility of using these systems in real human procedures, and also to improve and optimize our imaging systems using patient data.Finally, a novel force feedback control framework is presented as a solution to the lack of haptic feedback in the current clinically used surgicalrobots. The framework has been implemented on the da Vinci surgical system using the da Vinci Research Kit controllers and its performance hasbeen evaluated by conducting user studies.

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Prostate registration using magnetic resonance elastography for cancer localization (2015)

Noninvasive detection and localization of prostate cancer in medical imaging is an important, yet difficult task. Benefits range from diagnosis of cancer, to planning and guidance of its treatment. In order to characterize cancer and evaluate its localization in volumetric images, such as ultrasound or magnetic resonance imaging (MRI), their spatial correspondence with the "gold standard" provided by histopathology must be established.In this thesis, we propose a general framework for a multi-slice to volume registration that is applied to register a stack of sparse, unaligned two-dimensional histological slices to a three-dimensional volumetric imaging of the prostate. The approach uses particle filtering that allows deriving optimal pose parameters of the slices in a Bayesian approach.We then propose a novel registration method between in vivo and ex vivo MRI of the prostate to facilitate its registration to histopathology. The method incorporates elasticity information, acquired by magnetic resonance elastography (MRE), to generate a patient-specific biomechanical model of the prostate and periprostatic tissue.Next, we propose a registration method between preoperative MRI and intraoperative transrectal-ultrasound. The method can be incorporated with a robotic surgical system to augment the surgeon's visualization during robot-assisted prostatectomy. We also study the use of elasticity-based registration of ultrasound elastography and MRE.We then present an image processing approach for enhancing MRE data. The approach employs registration to compensate for motion of patients during the scan to improve the accuracy of the reconstructed elastogram. A super-resolution technique is employed to increase the resolution of the acquired images by utilizing unique properties of MRE.Finally, we develop a theory for optimization-based design of motion encoding in MRE that allows reducing scanning time and increasing signal-to-noise ratio of elasticity reconstruction. We formulate the displacement estimation of the mechanical wave as an experimental design problem, by which we quantify performance of sequences, and optimize multidirectional designs.The proposed methods have been evaluated in simulations and on a diverse set of clinical data. Results may pave the way for a broader clinical deployment of elastography and elastography-based image processing.

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Magnetic resonance elastography of prostate cancer (2013)

This work presents new approaches to in-vivo and ex-vivo human prostate cancer imaging using magnetic resonance elastography (MRE) – a method to non-invasively image tissue elasticity using magnetic resonance imaging (MRI). From a clinical perspective, stiffness correlates with underlying tissue disease processes and has been traditionally probed with palpation. Thus, diagnosis based on mechanical properties may have great implications in terms of staging of prostate cancer, monitoring disease progression, treatment planning and post treatment follow up. In MRE, mechanical shear waves generted by an external transducer are imaged using an MRI scanner. From the acquired wave field it is possible to reconstruct mechanical properties such as the elastic modulus based on the wave equation. In this work two MR compatible trans-perineal transducers are developed for imaging of the human prostate on a 3T MR scanner. A new MRI pulse sequence is also developed to acquire the three dimensional wave fieldinduced by these transducers. The methods are validated in quality assurance phantoms and volunteer repeatability studies. The system is used for a patient study and the results are compared to the gold standard (whole-mount histopathology marked with Gleason score). Similarly, a transducer is developed for ex-vivo prostate studies on a 7T MR scanner. After validation, prostate specimens of patients are examined and the results are compared to the Gleason score. The overall conclusion are: (i) trans-perineal excitation is well tolerated by the subjects, (ii) the transducers do not interfere with the MR acquisition, (iii) the three dimensional wave field are successfully captured using the new pulse sequence, (iv) phantom validation studies prove that the methods are in fact repeatable and that thestiffness values match with the manufacturer’s specifications, (v) patient motion and the standing wave pattern degrade the repeatability of the reconstructed images, (vi) the prostate gland stands out in the stiffness and shear strain images, (vii) the central gland and in particular the transition zone are stiffer than the peripheral zone, (viii) cancer could indeed be detected with MRE with an area under the receiver-operator-curve of approximately 0.7, and finally (ix) the chemical fixation process degrades the stiffness contrast.

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Prostate segmentation for medical interventions (2013)

Prostate cancer is the most prevalent type of cancer among men. Accurate delineation and appropriate visualization of the prostatic region can greatly affect treatment of prostate cancer and has the potential to reduce some of the treatment side-effects. The main goal of this research is to develop a prostate segmentation tool which is suitable to replace manual delineation. Manual segmentation, the current standard in procedures such as low dose rate prostate brachytherapy, is tedious, time consuming and observer dependent. We propose a 3D semi-automatic segmentation tool to overcome these limitations. To show the clinical value of this method we perform extensive dosimetric evaluation on in-vivo ultrasound images. This tool is currently being clinically used as part of the prostate brachytherapy treatment procedure at the BC Cancer Agency.Ultrasound is the common modality for imaging the prostate. Although safe and simple to use, it can not always allow the prostate to be reliably delineated. Vibro-elastography is a relatively new imaging method which is used to characterize mechanical properties of tissue. We investigate the suitability of vibro-elastography for visualizing the prostate. We compare in-vivo B-mode ultrasound and vibro-elastograpy images with the gold standard MRI in terms of contrast, edge visibility and the shape and size of the gland as seen in these images. Based on our results we develop a 3D automatic prostate segmentation tool in which, in addition to B-mode, information from vibro-elastography images is used in an iterative model-based segmentation approach.We conclude this work by studying the visibility of cancer itself in vibro-elastography images. Areas suspected for cancer are manually marked on the images and the results are compared to the marked cancer in registered pathology slices. Our preliminary results show that vibro-elastography has the potential to be used for detecting prostate cancer; however, we suggest a combined use of various modalities or image types to improve cancer detection.

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Characterization of implanted seed orientation and displacement dynamics with application to the design of non-uniform source strength treatment plans for prostate brachytherapy (2012)

Low dose rate prostate brachytherapy is one of the most effective treatments for prostate cancer currently available. It involves the implantation of approximately one hundred small radioactive sources, or ‘seeds’, into the prostate gland. This is accomplished by depositing the seeds transperineally via 16-30 long needles. In British Columbia, over three thousand patients have been treated since 1998 using this technique, and fewer than 10% have suffered a recurrence to date. One of the principal challenges in low dose rate prostate brachytherapy is the limited reliability with which precise doses to the prostate and surrounding organs can be achieved. This is due both to the difficulty in accurately delivering the seeds to their planned positions, as well as movement of the seeds in the post-implant period during the resolution of procedure-induced edema. This uncertainty can lead to undetected deficits in the dose necessary to control the cancer. As patients with more advanced disease are being considered for brachytherapy, these deficits may have greater consequences on oncological outcomes. Treatment uncertainty also increases the risk of side effects, which have the potential to be severe.The overall aim of this thesis is to improve the scope and accuracy with which the dose distribution of stranded seeds can be measured after implant. This involved the development of an algorithm to uniquely identify seeds in post-implant CT data, along with a method to determine their orientation to improve dosimetric accuracy. An analysis of the displacement and migration patterns of seeds in the interval during the resolution of prostate edema was also undertaken. These results identified dosimetric deficiencies and modes of seed loss which have the potential to be rectified by the use of implants containing seeds of non-uniform strength (‘mixed-activity’ implants). Such treatments use fewer needles and may also reduce the incidence of treatment related urinary morbidity. Although the concept of mixed-activity implants is not novel, the algorithm developed to identify seeds after implant enables the post-implant assurance of their dosimetric quality in a clinically feasible way. This thesis concludes with a study investigating the dosimetric benefits of mixed-activity implants.

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Meshing and rendering of patient-specific deformation models with application to needle insertion simulation (2010)

Tissue deformation is common during many medical interventions. An accurate simulation of these procedures necessitates accounting for tissue displacements by modeling tissue deformation and medical tool interaction. In minimally-invasive procedures, due to lack of visibility, physicians rely on haptic feedback and medical imaging to assess the immediate anatomical configuration and relative medical tool position. These procedures are often difficult to learn and therefore extensive training becomes essential.Computerized training systems offer an alternative to cadavers and training on patients. To accurately model the tissue deformation, most such systems require a mesh representation of the anatomy. To replicate the medical imaging feedback offered during procedures, a realistic image simulation approach is also needed. In this thesis, a novel energy-based meshing technique taking medical images and producing desirable meshes for the finite element method is introduced. This method employs an image-based discretization energy combined with a geometry-based element quality energy. The former promotes each mesh element to cover similar intensity image regions, while the latter ensures the element suitability for finite element simulation. A method that can mimic realistic B-mode ultrasound images under deformation is also presented in this thesis. This method first maps the pixels of an image from a deformed mesh configuration back to the nominal configuration, and then interpolates them in a B-mode voxel volume reconstructed a priori.Needle insertion is involved in several medical procedures. These percutaneous procedures will benefit significantly from advances in simulating needle-tissue interaction, for which a 3D model is proposed in this thesis. Simulating needle flexibility is achieved fast and accurately using a novel approach employing torsional springs. The needle insertion simulation with haptic feedback is presented for a training scenario for prostate brachytherapy, where simulated ultrasound images coupled with deformation are also displayed. A scheme to generate patient models for this system is also devised using both the conventional meshing techniques in the literature and the proposed variational meshing method.

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Methods for the estimation of the tissue motion using digitized ultrasound echo signals (2010)

Tissue motion estimation in ultrasound images plays a central role in many modern signal processing applications, including tissue characterization, strain and velocity imaging, and tissue viscoelasticity imaging. Therefore, the performance of tissue motion estimation is of significant importance. Also, its computational cost determines if it can be implemented in real-time so that it can be used clinically. This thesis presents several efficient methods for accurate estimation of tissue motion using digitized ultrasound echo signals.First, sample tracking algorithms are presented as a new class of motion estimators. These algorithms are based on the tracking of individual samples using a continuous representation of the reference echo signal. Simulations and experimental results on tissue mimicking phantoms show that sample tracking algorithms significantly outperform common algorithms in terms of accuracy, precision, sensitivity, and resolution. However, their performance degrades in the presence of noise.To improve the performance of motion estimation in multi-dimensions, pattern matching interpolation techniques are studied and new interpolation techniques are presented. Simulation and experimental results show that, with small computational overhead, the proposed interpolation techniques significantly improve the accuracy and the precision of motion estimation in both 2D and 3D. Employing these techniques, real-time 2D motion tracking software is developed. Furthermore, the performance of the proposed 2D estimators is compared with that of 2D tracking using angular compounding. The results show that the proposed interpolation methods bring the performance of pattern matching techniques close to that of 2D compound tracking. Finally, angular compounding is combined with custom pulse sequencing and delay cancellation techniques to develop a system that estimates the motion vectors at very high frame rates (> 500 Hz) in real-time. The application of the system in the study of the propagation of mechanical waves for tissue characterization is also presented.

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Needle insertion simulation and path planning for prostate brachytherapy (2009)

Low dose rate prostate brachytherapy has emerged as a treatment option forlocalized prostate cancer. During prostate brachytherapy, tiny radioactivecapsules - seeds - are implanted inside the tissue using long needles. The quality of the treatment depends on the accuracy of seed delivery to their desired positions. Prostate deformation and displacement during insertion and lack of sufficient visual feedback complicate accurate targeting and necessitates extensive training on the part of the physician. Needle insertion simulators can be useful for physician training. In addition, insertion of theneedle with optimized parameters can compensate for prostate deformation,can decrease the targeting errors and, subsequently, can increase thepost-treatment quality of life of the patients. Therefore, needle insertionsimulation and path planning have gained a lot of attention in the research community in the past decade. Moreover, several robots have been designed for brachytherapy; however, they are yet to be coupled with proper needle insertion path planning algorithms.In this thesis, steps toward a path planning algorithm for needles are taken. An optimization method is proposed that updates the initial insertion parameters of a rigid needle, iteratively, based on the simulated positions of the targets, in order to reduce the error between the needle and several targets in a 3D tissue model. The finite element method is used in the needle insertion simulator. The simulator requires a model for the needle-tissue interaction. Therefore, an experimental method has been developed to identify the force model and the tissue elasticity parameters usingmeasurements of insertion force, tissue displacement and needle position.Ultrasound imaging is used to measure tissue displacement. Ultrasound is a common imaging modality in the operating room and does not need beads or markers to track the tissue motion. Therefore, the experimental method can be used in patient studies. The needle-tissue modeling method and insertion parameter optimization were validated in experiments with tissue-mimicking phantoms.In order to facilitate the accommodation of needle flexibility for future applications, three flexible needle models have been compared. Based on these comparisons, it was determined that an efficient and accurate angular spring model is best suited for future studies.

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On the identification of mechanical properties of viscoelastic materials (2009)

Commonly used medical imaging techniques can render many properties of the anatomy or function, but are still limited in their ability to remotely measure tissue mechanical properties such as elasticity and viscosity. A remote and objective palpation function would help physicians in locating possible tumors or malignancies. The branch of medical imaging that characterizes tissues mechanical properties in a non-invasive manner has enjoyed increasing interest in the past two decades. The basic principle is to apply an excitation, such as tissue compression, to a region of interest and measure the resulting tissue deformation. Tissue mechanical properties can then be inferred from the observed deformation at multiple locations in the region, and the properties can be displayed as an image. If the excitation is dynamic, the deformation is considered as a motion field that varies in time and location over the region of interest. Ultrasound is particularly well suited for measuring motion fields due to its ability to image in real-time, low cost, low risk and ease-of-accessibility. The focus of this thesis is the estimation of the viscoelastic parameters such as Young's modulus, viscosity and relaxation-time. For this purpose, a motion estimation method is proposed to measure axial tissue displacements from the peak of the ultrasound radio frequency signals. The displacements can be further processed to identify the mechanical properties. Two methods were developed: the first one is based on a one dimensional Voigt's model of soft tissue and the second one is based on a finite element model. In the first method, a single frequency or wide-band excitation is applied to the tissue and the local relaxation-time is recovered from the phase difference between the strains or displacements. In this method, the elasticity can also be reconstructed from the magnitudes of the spectra. In the second approach, a novel dynamic finite element model is proposed for the incompressible soft materials. An inverse problem of viscoelasticity is solved iteratively to reconstruct the viscosity and elasticity based on a two or three dimensional model. The theoretical aspect of compressional elastography and longitudinal wave propagation is investigated. It is shown to be feasible to apply dynamic or transient compressional excitation to recover the dynamic properties of soft tissue.

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System for vessel characterization : development and evaluation with application to deep vein thrombosis diagnosis (2008)

A system for vessel characterization aimed at detecting deep vein thrombosis (DVT) in the lower limbs has been developed and evaluated using ultrasound image processing, location and force sensors measurements, blood flow information and a protocol based on the current clinical standard, compression ultrasound. The goal is to provide an objective and repeatable system to measure DVT in a rapid and standardized manner, as this has been suggested in the literature as an approach to improve overall detection of the disease.The system uses a spatial Kalman filter-based algorithm with an elliptical model in the measurement equation to detect vessel contours in transverse ultrasound images and estimate ellipse parameters, and temporal constant velocity Kalman filters for tracking vessel location in real-time. The vessel characterization also comprises building a 3-D vessel model and performing compression and blood flow assessments to calculate measures that indicate the possibility of DVT in a vessel. A user interface designed for assessing a vessel for DVT was also developed.The system and components were implemented and tested in simulations, laboratory settings, and clinical settings. Contour detection results are good, with mean and rms errors ranging from 1.47-3.64 and 3.69-9.67 pixels, respectively, in simulated and patient images, and parameter estimation errors of 5%. Experiments showed errors of 3-5 pixels for the tracking approaches. The measures for DVT were evaluated, independently and integrated in the system. The complete system was evaluated, with sensitivity of 67-100% and specificity of 50-89.5%. System learnability and memorability were evaluated in a separate user study, with good results.Contributions include a segmentation approach using a full parameter ellipse model in an extended Kalman filter, incorporating multiple measurements, an alternate sampling method for faster parameter convergence and application-specific initialization, and a tracking approach that includes a sub-sampled sum of absolutes similarity calculation and a method to detect vessel bifurcations using flow data. Further contributions include an integrated system for DVT detection that can combine ultrasound B-mode, colour flow and elastography images for vessel characterization, a system interface design focusing on usability that was evaluated with medical professionals, and system evaluations through multiple patient studies.

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Master's Student Supervision (2010 - 2018)
An investigation of multi-modal gaze-supported zoom and pan interactions in ultrasound machines (2017)

We are investigating the potential and the challenges of integrating eye gaze tracking support into the interface of ultrasound machines used for routine diagnostic scans by sonographers. In this thesis, we follow a user-centred approach by first conducting a field study to understand the context of the end user. As a starting point to a gaze-supported interface, we focus on the zoom functions of ultrasound machines. We study gaze-supported approaches for the often-used zoom function in ultrasound machines and present two alternatives, One-step Zoom (OZ) and Multi-step Zoom (MZ). A state-based analysis on the zoom functions in ultrasound machines is presented followed by a state-based representation of the gaze-supported alternatives. The gaze-supported state representation extends the manual-based interaction by implicitly integrating gaze input to OZ and offering a gaze-supported alternative to moving the zoom box in MZ. Evaluations of the proposed interactions through a series of user studies, seventeen non-sonographers and ten sonographers, suggest an increased cognitive demand and time on task compared to the conventional manual-based interaction. However, participants also reported an increased focus on main tasks using the gaze-supported alternative, which could offer benefit to novice users. They also report a lowered physical interaction as the gaze input replaces some functions of the manual input.

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Towards liver shear wave vibro-elastography : method repeatability and image registration technique (2017)

Liver fibrosis is a largely prevalent concern in Canada and world-wide, due to high rates of Hepatitis, fatty liver disease, alcoholism, as well as several other possible causes. It is currently diagnosed and staged by performing biopsies or by tissue elasticity measurements referred to as elastography. Elastography methods are a relatively new means of measuring the mechanical properties of soft tissue non-invasively by measuring and processing the propagation of shear waves through the body. The Robotics and Control Laboratory at the University of British Columbia has developed an elastography technique, Vibro-elastography, that can quantitatively measure soft tissue stiffness in real time. It has previously been applied to prostate and breast pathologies. It is now being developed and optimized for liver applications.To validate Vibro-elastography as a new diagnostic tool, a comparison study should be performed on a clinical population. This work sets out to lay out the prerequisites needed to implement a full clinical study. It starts out with a repeatability study using a tissue phantom to ensure repeatable results and compare our results to manufacturer stiffness values. In this work, we compare the precision of several different implementations of Vibro-elastography including the placement of the excitation source, data acquisition techniques and single versus multi-frequency excitation. Most of the implementations resulted in good, repeatable results, regardless of exciter placement. The quality of wave propagation deteriorated with depth as expected, but elasticity results remained repeatable even at deeper regions of interest. The parameters are selected and designed for the use on the liver.Finally, a registration pipeline and initial case trial has been presented as a suggested means of comparing the elastography data obtained using Vibro-elastography and any elastography measures that can be obtained from a magnetic resonance system. Using manual fiducial vessel markers and applying an Iterative Closest Point registration process results in a quick alignment of the ultrasound and MRI volumes with registration error less than 20 mm.

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On the development of a heart motion compensation system on the da Vinci research kit for minimally invasive surgery on the beating heart (2015)

This thesis describes the development of a heart motion compensation system on the da Vinci Research Kit for coronary artery bypass surgery. With this teleoperation robotic platform, minimally invasive surgery on a beating heart could be performed on an already clinically prevalent system. Semi-automation of the slave manipulators of the robot is introduced as they track the surface of the beating heart. The surgeons' regular teleoperation commands are superimposed on the automated trajectory. To achieve a virtually stabilized environment, a novel concept of maintaining the camera fixed relative to the heart target is proposed. The preliminary research question is whether the robot is capable of tracking the highly dynamic heart motion. System identification was performed on the seven degree of freedom da Vinci slave manipulators, and an open loop controller was developed. The controller is based on spectral line decomposition and the assumption of a periodic trajectory. It successfully commanded the slave manipulators to track an actual three dimensional heart trajectory with submillimetre error. Experiments were conducted with expert robotic users to evaluate surgeons’ ability to perform tasks on a moving target emulating the beating heart, with very promising outcomes. The number of missed targets decreased from 37% to 13% when compensation was enabled, the number of hit targets increased from 26% to 41%, and completion time decreased. A second generation system was developed which includes real time motion measurement commanding the robot. Results from user studies with expert surgeons performing bimanual suturing on moving targets with the new system support the motion compensation. They also show the significance of motion measurement errors. As an added safety, a virtual fixture was implemented to protect the heart from accidental collisions with the instrument tips. User studies were conducted to validate the efficacy of the fixture. To expedite controller development, an interface was developed between Matlab Simulink and the C++ code that runs the da Vinci Research Kit. This allows on-the-fly testing of controllers which could be designed and developed in the convenient Simulink environment. Future work will be include closed loop control, improved experiment design, and the incorporation of electrocardiogram signals.

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Automatic pathology of prostate cancer in whole mount slides incorporating individual gland classification (2014)

This thesis presents an automatic pathology (AutoPath) approach to detect prostatic adenocarcinoma based on the morphological analysis of high resolution whole mount histopathology images of the prostate. We are proposing a novel technique of labeling individual glands as benign or malignant exploiting only gland specific features. Two new features, the Number of Nuclei Layers and the Epithelial Layer density are proposed here to label individual glands. To extract the features, individual gland and nuclei units are segmented automatically. The nuclei units are segmented by employing a marker-controlled watershed algorithm. The gland units are segmented by consolidating their lumina with the surrounding layers of epithelium and nuclei. The main advantage of this approach is that it can detect individual malignant gland units, irrespective of neighboring histology and/or the spatial extent of the cancer. Therefore, a more sensitive annotation of cancer can be achieved by the proposed AutoPath technique, in comparison to the current clinical protocol, where the cancer annotation is performed at the regional macro level instead of glandular level technique.We have also combined the proposed gland-based approach with a regional approach to perform automatic cancer annotation of the whole mount images. The proposed algorithm performs the task of cancer detection in two stages: at first with pre-screening of the whole mount images in a low resolution (5x), and then ii) a finer annotation of the cancerous regions by labeling individual glands at a higher magnification (20x). In the first stage, the probable cancerous regions are classified using a random forest classifier that exploits the regional features of the tissue. In the second stage, gland specific features are used to label individual gland units as benign or malignant. The strong agreement between the experimental results and the pathologist's annotation corroborates the effectiveness of the proposed technique. The algorithm has been tested on 70 images. In a 10-fold cross validation experiment it achieved average sensitivity of 88%, specificity of 94% and accuracy of 93%. This surpasses the accuracy of other methods reported to date.

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Towards real-time tissue surface tracking with a surface-based extended kalman filter for robotic-assisted minimally invasive surgery (2014)

The use of registered intra-operative to pre-operative imaging has been proposed for many medical interventions, with the goal of providing more informed guidance to the physician. The registration may be difficult to carry out in real-time.Therefore, it is often necessary to track the motion of the anatomy of interest in order to maintain a registration.In this work, a surface based Extended Kalman Filter (EKF) framework is proposed to track a tissue surface based on temporal correspondences of 3D features extracted from the tissue surface. Specifically, an initial 3D surface feature map is generated based on stereo matched Scale Invariant Feature Transform (SIFT) feature pairs extracted from the targeted surface. For each consecutive frame, the proposed EKF framework is used to provide 2D temporal matching guidance in both stereo channels for each feature in the surface map. The 2D feature matching is carried out based on the Binary Robust Independent Elementary Feature (BRIEF) descriptor. If the temporal match is successful in both stereo channels, the stereo feature pair can be used to reconstruct the feature location in 3D. The newly measured 3D locations drive the EKF update to simultaneously estimate the current camera motion states and the feature locations of the 3D surface map. The framework is validated on ex vivo porcine tissue surface and in vivo prostate surface during a da Vinci radical prostatectomy. The peak and mean fiducial errors are 2.5 mm and 1.6 mm respectively.Compared to other methods, the surface based EKF framework can provide a reliable 2D feature matching guidance for each feature in the 3D surface map. This maintains a chance to relocate a feature that was lost for a significant period of time. Such a surface based framework provides persistent feature tracking over time, which is crucial to drift free surface tracking. With implementation on a Graphic Unit Processor (GPU), real time performance is achieved.

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A research platform for ultrasonic elastrography based targeted prostate biopsy (2013)

No abstract available.

A system for intraoperative transrectal ultrasound imaging in robotic-assisted laparoscopic radical prostatectomy (2011)

This thesis describes a system for intraoperative transrectal ultrasound imaging inrobotic-assisted laparoscopic radical prostatectomy, and related image registrationwork.First, a novel method for registering three-dimensional ultrasound data to anexternal coordinate frame is presented. The method uses a registration tool pressedagainst an air-tissue boundary to provide common target points in the the ultrasound frame and the external frame. This method has two applications in our system: registering the ultrasound data captured by the system to a laparoscopic stereo camera to allow augmented-reality style overlays in laparoscopic or robotic surgery, and registering the system to the da Vinci Surgical System so the ultrasoundimaging arrays can automatically track the da Vinci tools during surgery. In an initial feasibility study, the method was used to register a mechanical three-dimensional ultrasound transducer to high-disparity stereo cameras through a tissue phantom. Average registration error was found to be 1.69 ± 0.60 mm. Accuracy of localizing ultrasound fiducials pressed against an air-tissue boundary was found to range from 0.54 mm to 1.04 mm. In a second study, the method was used to register three-dimensional transrectal ultrasound data to a da Vinci stereo endoscope. In this study, fiducials imaged at multiple registration tool positions were incorporated into a single registration. Registration error imaging through a tissue phantom ranged from 3.85 ± 1.76 mm using one registration tool position to 1.82 ± 1.03 mm using four positions. Registrationerror imaging through an ex-vivo porcine liver tissue sample ranged from 2.36 ± 1.01 mm using one registration tool position to 1.51 ± 0.70 mm using four positions.

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Deformable prostate registration from MR and TRUS images using surface error driven FEM models (2011)

TransRectal Ultrasound (TRUS) is used for image guidance during prostate biopsy and for treatment planning of brachytherapy due to low cost and accessibility in operating room. However, tumors have better visibility in Magnetic Resonance (MR) images. The fusion of TRUS and MR images of the prostate can aid with the diagnosis and treatment planning for prostate cancer and with post-brachytheraphy quality assurance. We developed a 3D deformable registration method using the segmentations obtained from TRUS and MR images and a biomechanical model that employs stiffness values derived from elastography. The segmented source volume is meshed and a linear finite element model is created for it. This volume is deformed to the target image volume by applying surface forces computed by assuming a negative relative pressure between the non-overlapping and the overlapping regions of the volumes. This pressure drives the model to increase the volume overlap until the surfaces are aligned. We tested our algorithm on prostate surfaces extracted from postoperative MR and TRUS images for 14 patients and pre-operative MR and TRUS images for 4 patients, using a model with elasticity within the range reported in the literature for the prostate. We used three evaluation metrics for validation: the Dice Similarity Coefficient (DSC) (ideally equal to 1.0), the volume change in source surface during registration, and the Target Registration error (TRE) defined as the mean distance between landmarks such as urethrae and calcifications. For post-operative images, we obtained a DSC of 0.96±0.02 and a TRE of 1.5±1.4mm. The change in the volume of the source surface was 1.5±1.4%. For pre-operative images, we obtained the DSC of 0.96±0.01 and a TRE of 1.3±0.8mm. The change in the volume of the source surface was -0.9±0.2%. Our results show that this method is a promising tool for physically-based deformable surface registration. We also used our technique to register ultrasound strain images to free mount histo-pathology images with the goal of correlating cancer with areas of low strain. This was done using relative stiffness values derived from vibroelastography data. We also performed Computed Tomography (CT) and Ultrasound (US) kidney surface registration using this technique.

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Feature-based registration of preoperative CT to intraoperative 3-D ultrasound in laparoscopic partial nephrectomy using a priori CT segmentation (2011)

Robotic laparoscopic partial nephrectomy is a state-of-the-art procedure for the excision of renal tumours. The challenges of this surgery along with the stereoscopic interface to the surgeon make it an ideal candidate for image guidance. We propose bringing pre-operative computed tomography data to the patient's coordinate system using three-dimensional intraoperative back ultrasound. Since computed tomography and ultrasound images represent like anatomical information quite differently, we perform a manual segmentation of the computed tomography before the operation and a semi-automatic segmentation of the ultrasound intra-operatively. The segmentation of the kidney boundary facilitates a feature-based registration strategy.Semi-automatic segmentation of kidney ultrasound images is difficult because the edges with large gradient values do not correspond to the capsule boundary seen in computed tomography. The desired edges are actually quite faint in ultrasound and poorly detected by common edge methods such as the Canny approach.After trying a number of approaches, the best results were obtained using a novel interacting multiple-model probabilistic data association filter to select edges from ultrasound images that were filtered for phase congruency. The manual segmentation of the prior is used to guide edge detection in ultrasound. Experiments on seven pre-operative patient datasets and one intra-operative patient dataset resulted in a mean volume error ratio of 0.80 +/- 0.13 from after registration to before registration. These results came after the implementation and evaluation of numerous other approaches, including radial edge filters, the covariance matrix adaptation evolution strategy, and a deformable approach using geodesic active contours.The main contribution of this work is a method for the registration of the pre-operative planning data from computerized tomography to the intraoperative ultrasound. For clinical use, this method requires some form of calibration with the laparoscopic camera and integration with surgical visualization tools. Through integration with emerging technologies, the approach presented here can one day augment the surgical field-of-view and guide the surgeon around important anatomical structures to the tissue that must be excised.

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Ultrasound registration and tracking for robot-assisted laproscopic surgery (2011)

In the past two decades, there has been considerable research interest in medical image registration during surgery. The overlay of medical images over the images from a surgical camera allows the surgeon to see sub-surface features such as tumor boundaries and vasculature. Ultrasound imaging is a prime candidate for medical image registration, as it is a real-time imaging modality and therefore is commonly-used for intraoperative surgical guidance. Prior technologies that attempted ultrasound-based registration have used external trackers in order to establish a geometric correspondence between the surgical cameras and the ultrasound probes; this requires probe and camera calibration, which is time-consuming, requires additional equipment, and adds additional sources of error to the registration.Another problem is how to maintain a registration between the ultrasound image and the underlying tissues, since tissues will move and deform from patient breathing and heartbeat, and from surgical instrument interaction with tissues. In order to overcome this, the underlying tissue should be tracked, and previously acquired ultrasound images should be registered and moved with the tracked tissue. Prior work has had limited success in providing a real-time solution for estimating local tissue deformation and movement; furthermore, there has been no work in estimating the accuracy of maintaining a registration --- that is, the accuracy of the registration after having been moved with the tracked tissue. In this work, we establish an image registration method between ultrasound images and endoscopic stereo-cameras using a novel registration tool; this method does not require external tracking or ultrasound probe calibration, thus providing a simple method for performing a registration. In order to maintain an image registration over time, we developed a tissue tracking framework. Its key innovation is in achieving real-time tracking of a dense tissue surface map. We use the STAR detector and Binary Robust Independent Elementary Features and compare their performance to prior tissue feature tracking methods, showing that they perform significantly faster while still managing to track the tissue at high densities. Experiments are performed on ex-vivo bovine heart, kidney, and porcine liver tissues, and initial results show that registrations can be maintained within 3 mm.

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Viscoelastic imaging methods using acoustic radiation force (2011)

Elastography is a method of imaging the viscoelastic properties of soft tissue and similar media. It can be used for identifying various forms of cancer and fibrosis in soft tissue. Elastography can thus aid in diagnosis of such diseases, and in treatment procedures, such a biopsy needle guidance. Acoustic radiation force (ARF) imaging is one form of elastography whereby the ARF of focused ultrasound displaces the medium at an internal, localised position. The same ultrasound system can be used to monitor the displacement, from which the viscoelastic properties can be recovered.This work presents a new ARF imaging method, called axial relaxation imaging, that uses transfer function techniques. The relaxation response at a point in the medium is monitored after a period of ARF application. By assuming the response corresponds to a negative step response of a linear system, the relative force-displacement transfer function is computed. This is then related to a Voigt model over a range of frequencies to obtain a relative elastic parameter and a frequency-dependent viscous parameter governed by a power law.The method was applied to homogeneous phantoms made with different gelatine concentrations. Relative elastic parameters of 1, 2.3 and 4.4 and relative viscous parameters of 1, 1.8 and 3.0 were obtained for 2, 3 and 4 wt% gelatine concentrations, respectively, with consistent results between phantoms of the same type and agreement with values from other estimation techniques. The viscous power law frequency dependencies were governed by flow index values of –0.10, –0.14 and –0.18, respectively. The good separation between parameters in the results shows the method holds potential for application to tissue characterisation.

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A robotic needle guide for prostate brachytherapy with pre-operative to intra-operative prostate volumes registration (2010)

The conventional prostate brachytherapy approach is limited by needle positioning accuracy, needle trajectory option, and prostate motion and deformation between the pre-operative volume study and the seed implant procedure. These limitations increase the risks of post implant complications. In this thesis we develop a robotic needle guide to improve prostate brachytherapy needle placement accuracy and trajectory option as well as a pre-operative to intra-operative prostate volume registration algorithm to address the issue of prostate motion and deformation.Our four degrees of freedom robot provides X-Y axes translational accuracy of 0.12 and 0.1 mm compared to the 5 mm accuracy of the standard needle guide. The robot also provides yaw and pitch angulations with 0.05 degrees accuracy which can be used to reach prostate regions blocked by pubic arch interference. The robot is adaptable to conventional brachytherapy apparatus without adding the clinical procedure time and can be used manually in the case of electronic control failure.The registration approach is based on fitting prostate surfaces into ellipsoids. Pre-operative and intra-operative sagittal view-based volume data are contoured using a novel semi automatic sagittal view-based segmentation algorithm. The resulting contours are fit into ellipsoids whose parameters - centers, orientations, and radii - are used to calculate the registration matrix. The accuracy of the registration algorithm was compared with Optotrak measurement as the gold standard and with the Iterative Closest Point (ICP) algorithm. The result shows that the orientation of the ellipsoid fit is sensitive to user initialization points causing up to 5 mm translational errors and 5.5 degrees angular error. The comparison with ICP shows that the ellipsoid fitting based algorithm is faster but less accurate.

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