My research and teaching Interest is Computer Integrated Surgery. This is a fascinating and complex field that covers medical imaging, image computing, scientific visualization, surgical planning and navigation, robotics, biosensors and, perhaps most importantly, integration of all these into workable clinical systems and translating them to clinical use. I further specialize in robot-assisted minimally invasive percutaneous (through the skin) surgeries performed under real-time image guidance, with primary application in the detection and treatment of cancer. Please visit our Laboratory for Percutaneous Surgery, or as we call it affectionately: the Perk Lab, online.
This will count as one of your downloads.
You will have access to both the presentation and article (if available).
METHODS: Ultrasound data was collected from nine healthy volunteers. Images were manually segmented. To accommodate for consecutive input images, the ultrasound images were exported along with previous images stacked to serve as input for a modified U-net. Resulting output segmentations were evaluated based on the percentage of true negative and true positive pixel predictions.
RESULTS: After comparing the single to five-image input arrays, the three-image input had the best performance in terms of true positive value. The single input and three-input images were then further tested. The single image input neural network had a true negative rate of 99.79%, and a true positive rate of 63.56%. The three-image input neural network had a true negative rate of 99.75%, and a true positive rate of 66.64%.
CONCLUSION: The three-image input network outperformed the single input network in terms of the true positive rate by 3.08%. These findings suggest that using two additional input images consecutively preceding the original image assist the neural network in making more accurate predictions.
METHODS: Following a pre-filtering of each captured ultrasound image, the shadows cast by each transverse process bone is examined and contours which are likely posterior bone surface are kept. From these contours, a threedimensional volume of the bone surfaces is created in real-time as the operator acquires the images. The processing algorithm was implemented on the PLUS and 3D Slicer open-source software platforms.
RESULTS: The algorithm was tested with images captured using the SonixTouch ultrasound scanner, Ultrasonix C5-2 curvilinear transducer and NDI trakSTAR electromagnetic tracker. Ultrasound data was collected from patients presenting with idiopathic adolescent scoliosis. The system was able to produce posterior surface patches of the transverse process in real-time, as the images were acquired by a non-expert sonographer. The resulting transverse process surface patches were compared with manual segmentation by an expert. The average Hausdorff distance was 3.0 mm when compared to the expert segmentation.
CONCLUSION: The resulting surface patches are expected to be sufficiently accurate for driving a deformable registration between the ultrasound space and a generic spine model, to allow for three-dimensional visualization of the spine and measuring its curvature.
METHODS: The algorithm uses cascade of filters to remove low intensity pixels, smooth the image and detect bony edges. By applying first differentiation, candidate bony areas are classified. The average intensity under each area has a correlation with the possibility of a shadow, and areas with strong shadow are kept for bone segmentation. The segmented images are used to reconstruct a 3-D volume to represent the whole spinal structure around the transverse processes. RESULTS: A comparison between the manual ground truth segmentation and the automatic algorithm in 50 images showed 0.17 mm average difference. The time to process all 1,938 images was about 37 Sec. (0.0191 Sec. / Image), including reading the original sequence file.
CONCLUSION: Initial experiments showed the algorithm to be sufficiently accurate and fast for segmentation transverse processes in ultrasound for spinal curvature measurement. An extensive evaluation of the method is currently underway on images from a larger patient cohort and using multiple observers in producing ground truth segmentation.
METHODS: A pointer tool was designed for concurrent electromagnetic and optical tracking. Software modules were developed for automatic calibration of the measurement system, real-time error visualization, and analysis. The system was taken to an operating room to test for field distortion in a navigated breast surgery setup. Positional and rotational electromagnetic tracking errors were then calculated using optical tracking as a ground truth.
RESULTS: Our system is quick to set up and can be rapidly deployed. The process from calibration to visualization also only takes a few minutes. Field distortion was measured in the presence of various surgical equipment. Positional and rotational error in a clean field was approximately 0.90 mm and 0.31°. The presence of a surgical table, an electrosurgical cautery, and anesthesia machine increased the error by up to a few tenths of a millimeter and tenth of a degree.
CONCLUSION: In a navigated breast surgery setup, measurement and visualization of tracking error defines a safe working area in the presence of surgical equipment. Our system is available as an extension for the open-source 3D Slicer platform.
METHODS: We create a series of implicit functions, which represent simulated structures. These structures are sampled at varying resolutions, and compared to labelmaps with high sub-millimeter resolutions. We generate DVH and evaluate voxelization error for the same structures at different resolutions by calculating the agreement acceptance percentage between the DVH.
RESULTS: We implemented tools for analysis as modules in the SlicerRT toolkit based on the 3D Slicer platform. We found that there were large DVH variation from the baseline for small structures or for structures located in regions with a high dose gradient, potentially leading to the creation of suboptimal treatment plans.
CONCLUSION: This work demonstrates that labelmap and dose volume voxel size is an important factor in DVH accuracy, which must be accounted for in order to ensure the development of accurate treatment plans.
METHODS: Two different kinds of ultrasound machines were tested on three human subjects, using the same position tracker and software. Spinal curves were measured in the same reference coordinate system using both ultrasound machines. Lines were defined by connecting two symmetric landmarks identified on the left and right transverse process of the same vertebrae, and spinal curvature was defined as the transverse process angle between two such lines, projected on the coronal plane.
RESULTS: Three healthy volunteers were scanned by both ultrasound configurations. Three experienced observers localized transverse processes as skeletal landmarks and obtained transverse process angles in images obtained from both ultrasounds. The mean difference per transverse process angle measured was 3.00 ±2.1°. 94% of transverse processes visualized in the Sonix Touch were also visible in the Telemed. Inter-observer error in the Telemed was 4.5° and 4.3° in the Sonix Touch.
CONCLUSION: Price, convenience and accessibility suggest the Telemed to be a viable alternative in scoliosis monitoring, however further improvements in measurement protocol and image noise reduction must be completed before implementing the Telemed in the clinical setting.
METHODS: A modular handheld augmented reality viewbox was constructed from a tablet computer and a semi-transparent mirror. A consistent and precise self-calibration method, without the use of any temporary markers, was designed to achieve an accurate calibration of the system. Markers attached to the viewbox and patient are simultaneously tracked using an optical pose tracker to report the position of the patient with respect to a displayed image plane that is visualized in real-time. The software was built using the open-source 3D Slicer application platform's SlicerIGT extension and the PLUS toolkit.
RESULTS: The accuracy of the image overlay with image-guided needle interventions yielded a mean absolute position error of 0.99 mm (95th percentile 1.93 mm) in-plane of the overlay and a mean absolute position error of 0.61 mm (95th percentile 1.19 mm) out-of-plane. This accuracy is clinically acceptable for tool guidance during various procedures, such as musculoskeletal injections.
CONCLUSION: A self-calibration method was developed and evaluated for a tracked augmented reality display. The results show potential for the use of handheld image overlays in clinical studies with image-guided needle interventions.
METHODS: We propose a method that uses simulation and visual verification to design continuum tools that are patient and procedure specific. Our software module utilizes pre-operative scans and virtual threedimensional (3D) patient models to intuitively aid instrument design. The user specifies basic tool parameters and the parameterized tools and trocar are modeled within the virtual patient. By selecting and dragging the instrument models, the tools are instantly reshaped and repositioned. The tool geometry and surgical entry points are then returned as outputs to undergo optimization. We have completed an initial validation of the software by comparing a simulation of a physical instrument’s reachability to the corresponding virtual design.
RESULTS AND CONCLUSION: The software was assessed qualitatively by two neurosurgeons, who design tools for an intraventricular endoscopic procedure. Further, validation experiments comparing the design of a virtual instrument to a physical tool demonstrate that the software module functions correctly. Thus, our platform permits user-friendly, application specific design of continuum instruments. These instruments will give surgeons much more flexibility in developing future minimally invasive procedures.
METHODS: A commercial breast biopsy phantom with several inclusions was used. Location and shape of a lesion before and after mechanical deformation were determined using 3D ultrasound volumes. Tumor location and shape were estimated from initial contours and tracking data. The difference in estimated and actual location and shape of the lesion after deformation was quantified using the Hausdorff distance. Data collection and analysis were done using our 3D Slicer software application and PLUS toolkit.
RESULTS: The deformation of the breast resulted in 3.72 mm (STD 0.67 mm) average boundary displacement for an isoelastic lesion and 3.88 mm (STD 0.43 mm) for a hyperelastic lesion. The difference between the actual and estimated tracked tumor boundary was 0.88 mm (STD 0.20 mm) for the isoelastic and 1.78 mm (STD 0.18 mm) for the hyperelastic lesion.
CONCLUSION: The average lesion boundary tracking error was below 2mm, which is clinically acceptable. We suspect that stiffness of the phantom tissue affected the error measurements. Results will be validated in patient studies.
View contact details
No SPIE Account? Create one
