Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study

Potentially precancerous polyps detected with CT colonography (CTC) need to be removed subsequently, using an optical colonoscope (OC). Due to large colonic deformations induced by the colonoscope, even very experienced colonoscopists find it difficult to pinpoint the exact location of the colonoscope tip in relation to polyps reported on CTC. This can cause unduly prolonged OC examinations that are stressful for the patient, colonoscopist and supporting staff. We developed a method, based on monocular 3D reconstruction from OC images, that automatically matches polyps observed in OC with polyps reported on prior CTC. A matching cost is computed, using rigid point-based registration between surface point clouds extracted from both modalities. A 3D printed and painted phantom of a 25 cm long transverse colon segment was used to validate the method on two medium sized polyps. Results indicate that the matching cost is smaller at the correct corresponding polyp between OC and CTC: the value is 3.9 times higher at the incorrect polyp, comparing the correct match between polyps to the incorrect match. Furthermore, we evaluate the matching of the reconstructed polyp from OC with other colonic endoluminal surface structures such as haustral folds and show that there is a minimum at the correct polyp from CTC. Automated matching between polyps observed at OC and prior CTC would facilitate the biopsy or removal of true-positive pathology or exclusion of false-positive CTC findings, and would reduce colonoscopy false-negative (missed) polyps. Ultimately, such a method might reduce healthcare costs, patient inconvenience and discomfort.Comment: This paper was presented at the SPIE Medical Imaging 2014 conferenc

Six DOF Motion Estimation for Teleoperated Flexible Endoscopes Using Optical Flow: A Comparative Study

Colorectal cancer is one of the leading causes of cancer-related deaths worldwide, although it can be effectively treated if detected early. Teleoperated flexible endoscopes are an emerging technology to promote participation in these preventive screenings. Real-time pose estimation is therefore essential to enable feedback to the robotic endoscope's control system. Vision-based endoscope localization approaches are a promising avenue, since they do not require extra sensors on board the endoscopes. In this work, we compare several state-of-the-art algorithms for computing the image motion (optical flow), which is then used with a supervised learning strategy to provide an accurate estimate of the 6 degree of freedom endoscope motion. The method is validated using a robotically actuated endoscope in a human colon simulator, and represents a preliminary effort towards testing with clinical video data

Accurate and reliable segmentation of the optic disc in digital fundus images

We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE)

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Current engineering developments for robotic systems in flexible endoscopy

The past four decades have seen an increase in the incidence of early-onset gastrointestinal cancer. Because early-stage cancer detection is vital to reduce mortality rate, mass screening colonoscopy provides the most effective prevention strategy. However, conventional endoscopy is a painful and technically challenging procedure that requires sedation and experienced endoscopists to be performed. To overcome the current limitations, technological innovation is needed in colonoscopy. In recent years, researchers worldwide have worked to enhance the diagnostic and therapeutic capabilities of endoscopes. The new frontier of endoscopic interventions is represented by robotic flexible endoscopy. Among all options, self-propelling soft endoscopes are particularly promising thanks to their dexterity and adaptability to the curvilinear gastrointestinal anatomy. For these devices to replace the standard endoscopes, integration with embedded sensors and advanced surgical navigation technologies must be investigated. In this review, the progress in robotic endoscopy was divided into the fundamental areas of design, sensing, and imaging. The article offers an overview of the most promising advancements on these three topics since 2018. Continuum endoscopes, capsule endoscopes, and add-on endoscopic devices were included, with a focus on fluid-driven, tendon-driven, and magnetic actuation. Sensing methods employed for the shape and force estimation of flexible endoscopes were classified into model- and sensor-based approaches. Finally, some key contributions in molecular imaging technologies, artificial neural networks, and software algorithms are described. Open challenges are discussed to outline a path toward clinical practice for the next generation of endoscopic devices

Endoscopic Optical Coherence Tomography: Design and Application

This thesis presents an investigation on endoscopic optical coherence tomography (OCT). As a noninvasive imaging modality, OCT emerges as an increasingly important diagnostic tool for many clinical applications. Despite of many of its merits, such as high resolution and depth resolvability, a major limitation is the relatively shallow penetration depth in tissue (about 2∼3 mm). This is mainly due to tissue scattering and absorption. To overcome this limitation, people have been developing many different endoscopic OCT systems. By utilizing a minimally invasive endoscope, the OCT probing beam can be brought to the close vicinity of the tissue of interest and bypass the scattering of intervening tissues so that it can collect the reflected light signal from desired depth and provide a clear image representing the physiological structure of the region, which can not be disclosed by traditional OCT. In this thesis, three endoscope designs have been studied. While they rely on vastly different principles, they all converge to solve this long-standing problem. A hand-held endoscope with manual scanning is first explored. When a user is holding a hand- held endoscope to examine samples, the movement of the device provides a natural scanning. We proposed and implemented an optical tracking system to estimate and record the trajectory of the device. By registering the OCT axial scan with the spatial information obtained from the tracking system, one can use this system to simply ‘paint’ a desired volume and get any arbitrary scanning pattern by manually waving the endoscope over the region of interest. The accuracy of the tracking system was measured to be about 10 microns, which is comparable to the lateral resolution of most OCT system. Targeted phantom sample and biological samples were manually scanned and the reconstructed images verified the method. Next, we investigated a mechanical way to steer the beam in an OCT endoscope, which is termed as Paired-angle-rotation scanning (PARS). This concept was proposed by my colleague and we further developed this technology by enhancing the longevity of the device, reducing the diameter of the probe, and shrinking down the form factor of the hand-piece. Several families of probes have been designed and fabricated with various optical performances. They have been applied to different applications, including the collector channel examination for glaucoma stent implantation, and vitreous remnant detection during live animal vitrectomy. Lastly a novel non-moving scanning method has been devised. This approach is based on the EO effect of a KTN crystal. With Ohmic contact of the electrodes, the KTN crystal can exhibit a special mode of EO effect, termed as space-charge-controlled electro-optic effect, where the carrier electron will be injected into the material via the Ohmic contact. By applying a high voltage across the material, a linear phase profile can be built under this mode, which in turn deflects the light beam passing through. We constructed a relay telescope to adapt the KTN deflector into a bench top OCT scanning system. One of major technical challenges for this system is the strong chromatic dispersion of KTN crystal within the wavelength band of OCT system. We investigated its impact on the acquired OCT images and proposed a new approach to estimate and compensate the actual dispersion. Comparing with traditional methods, the new method is more computational efficient and accurate. Some biological samples were scanned by this KTN based system. The acquired images justified the feasibility of the usage of this system into a endoscopy setting. My research above all aims to provide solutions to implement an OCT endoscope. As technology evolves from manual, to mechanical, and to electrical approaches, different solutions are presented. Since all have their own advantages and disadvantages, one has to determine the actual requirements and select the best fit for a specific application.</p

Exploring gastrointestinal variables affecting drug and formulation behavior: methodologies, challenges and opportunities

Various gastrointestinal (GI) factors affect drug and formulation behavior after oral administration, including GI transfer, motility, pH and GI fluid volume and composition. An in-depth understanding of these physiological and anatomical variables is critical for a continued progress in oral drug development. In this review, different methodologies (invasive versus non-invasive) to explore the impact of physiological variables on formulation behavior in the human GI tract are presented, revealing their strengths and limitations. The techniques mentioned allow for an improved understanding of the role of following GI variables: gastric emptying (magnetic resonance imaging (MRI), scintigraphy, acetaminophen absorption technique, ultrasonography, breath test, intraluminal sampling and telemetry), motility (MRI, small intestinal/colonic manometry and telemetry), GI volume changes (MRI and ultrasonography), temperature (telemetry) and intraluminal pH (intraluminal sampling and telemetry)

Medical Robotics for use in MRI Guided Endoscopy

Interventional Magnetic Resonance Imaging (MRI) is a developing field that aims to provide intra-operative MRI to a clinician to guide diagnostic or therapeutic medical procedures. MRI provides excellent soft tissue contrast at sub-millimetre resolution in both 2D and 3D without the need for ionizing radiation. Images can be acquired in near real-time for guidance purposes. Operating in the MR environment brings challenges due to the high static magnetic field, switching magnetic field gradients and RF excitation pulses. In addition high field closed bore scanners have spatial constraints that severely limit access to the patient. This thesis presents a system for MRI-guided Endoscopic Retrograde Cholangio-pancreatography (ERCP). This includes a remote actuation system that enables an MRI-compatible endoscope to be controlled whilst the patient is inside the MRI scanner, overcoming the spatial and procedural constraints imposed by the closed scanner bore. The modular system utilises non-magnetic ultrasonic motors and is designed for image-guided user-in-the-loop control. A novel miniature MRI compatible clutch has been incorporated into the design to reduce the need for multiple parallel motors. The actuation system is MRI compatible does not degrade the MR images below acceptable levels. User testing showed that the actuation system requires some degree of training but enables completion of a simulated ERCP procedure with no loss of performance. This was demonstrated using a tailored ERCP simulator and kinematic assessment tool, which was validated with users from a range of skill levels to ensure that it provides an objective measurement of endoscopic skill. Methods of tracking the endoscope in real-time using the MRI scanner are explored and presented here. Use of the MRI-guided ERCP system was shown to improve the operator’s ability to position the endoscope in an experimental environment compared with a standard fluoroscopic-guided system.Open Acces

Iterative multi-path tracking for video and volume segmentation with sparse point supervision

Recent machine learning strategies for segmentation tasks have shown great ability when trained on large pixel-wise annotated image datasets. It remains a major challenge however to aggregate such datasets, as the time and monetary cost associated with collecting extensive annotations is extremely high. This is particularly the case for generating precise pixel-wise annotations in video and volumetric image data. To this end, this work presents a novel framework to produce pixel-wise segmentations using minimal supervision. Our method relies on 2D point supervision, whereby a single 2D location within an object of interest is provided on each image of the data. Our method then estimates the object appearance in a semi-supervised fashion by learning object-image-specific features and by using these in a semi-supervised learning framework. Our object model is then used in a graph-based optimization problem that takes into account all provided locations and the image data in order to infer the complete pixel-wise segmentation. In practice, we solve this optimally as a tracking problem using a K-shortest path approach. Both the object model and segmentation are then refined iteratively to further improve the final segmentation. We show that by collecting 2D locations using a gaze tracker, our approach can provide state-of-the-art segmentations on a range of objects and image modalities (video and 3D volumes), and that these can then be used to train supervised machine learning classifiers