320 research outputs found

    Laryngoscopic Image Stitching for View Enhancement and Documentation - First Experiences

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    One known problem within laryngoscopy is the spatially limited view onto the hypopharynx and the larynx through the endoscope. To examine the complete larynx and hypopharynx, the laryngoscope can be rotated about its main axis, and hence the physician obtains a complete view. If such examinations are captured using endoscopic video, the examination can be reviewed in detail at a later time. Nevertheless, in order to document the examination with a single representative image, a panorama image can be computed for archiving and enhanced documentation. Twenty patients with various clinical findings were examined with a 70 rigid laryngoscope, and the video sequences were digitally stored. The image sequence for each patient was then post-processed using an image stitching tool based on SIFT features, the RANSAC approach and blending. As a result, endoscopic panorama images of the larynx and pharynx were obtained for each video sequence. The proposed approach of image stitching for laryngoscopic video sequences offers a new tool for enhanced visual examination and documentation of morphologic characteristics of the larynx and the hypopharynx

    Automatic Workflow for Narrow-Band Laryngeal Video Stitching

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    In narrow band (NB) laryngeal endoscopy, the clinician usually positions the endoscope near the tissue for a correct inspection of possible vascular pattern alterations, indicative of laryngeal malignancies. The video is usually reviewed many times to refine the diagnosis, resulting in loss of time since the salient frames of the video are mixed with blurred, noisy, and redundant frames caused by the endoscope movements. The aim of this work is to provide to the clinician a unique larynx panorama, obtained through an automatic frame selection strategy to discard non-informative frames. Anisotropic diffusion filtering was exploited to lower the noise level while encouraging the selection of meaningful image features, and a feature-based stitching approach was carried out to generate the panorama. The frame selection strategy, tested on on six pathological NB endoscopic videos, was compared with standard strategies, as uniform and random sampling, showing higher performance of the subsequent stitching procedure, both visually, in terms of vascular structure preservation, and numerically, through a blur estimation metric

    Appearance Modelling and Reconstruction for Navigation in Minimally Invasive Surgery

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    Minimally invasive surgery is playing an increasingly important role for patient care. Whilst its direct patient benefit in terms of reduced trauma, improved recovery and shortened hospitalisation has been well established, there is a sustained need for improved training of the existing procedures and the development of new smart instruments to tackle the issue of visualisation, ergonomic control, haptic and tactile feedback. For endoscopic intervention, the small field of view in the presence of a complex anatomy can easily introduce disorientation to the operator as the tortuous access pathway is not always easy to predict and control with standard endoscopes. Effective training through simulation devices, based on either virtual reality or mixed-reality simulators, can help to improve the spatial awareness, consistency and safety of these procedures. This thesis examines the use of endoscopic videos for both simulation and navigation purposes. More specifically, it addresses the challenging problem of how to build high-fidelity subject-specific simulation environments for improved training and skills assessment. Issues related to mesh parameterisation and texture blending are investigated. With the maturity of computer vision in terms of both 3D shape reconstruction and localisation and mapping, vision-based techniques have enjoyed significant interest in recent years for surgical navigation. The thesis also tackles the problem of how to use vision-based techniques for providing a detailed 3D map and dynamically expanded field of view to improve spatial awareness and avoid operator disorientation. The key advantage of this approach is that it does not require additional hardware, and thus introduces minimal interference to the existing surgical workflow. The derived 3D map can be effectively integrated with pre-operative data, allowing both global and local 3D navigation by taking into account tissue structural and appearance changes. Both simulation and laboratory-based experiments are conducted throughout this research to assess the practical value of the method proposed

    Retrieval and Registration of Long-Range Overlapping Frames for Scalable Mosaicking of In Vivo Fetoscopy

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    Purpose: The standard clinical treatment of Twin-to-Twin Transfusion Syndrome consists in the photo-coagulation of undesired anastomoses located on the placenta which are responsible to a blood transfer between the two twins. While being the standard of care procedure, fetoscopy suffers from a limited field-of-view of the placenta resulting in missed anastomoses. To facilitate the task of the clinician, building a global map of the placenta providing a larger overview of the vascular network is highly desired. Methods: To overcome the challenging visual conditions inherent to in vivo sequences (low contrast, obstructions or presence of artifacts, among others), we propose the following contributions: (i) robust pairwise registration is achieved by aligning the orientation of the image gradients, and (ii) difficulties regarding long-range consistency (e.g. due to the presence of outliers) is tackled via a bag-of-word strategy, which identifies overlapping frames of the sequence to be registered regardless of their respective location in time. Results: In addition to visual difficulties, in vivo sequences are characterised by the intrinsic absence of gold standard. We present mosaics motivating qualitatively our methodological choices and demonstrating their promising aspect. We also demonstrate semi-quantitatively, via visual inspection of registration results, the efficacy of our registration approach in comparison to two standard baselines. Conclusion: This paper proposes the first approach for the construction of mosaics of placenta in in vivo fetoscopy sequences. Robustness to visual challenges during registration and long-range temporal consistency are proposed, offering first positive results on in vivo data for which standard mosaicking techniques are not applicable.Comment: Accepted for publication in International Journal of Computer Assisted Radiology and Surgery (IJCARS

    Periapical abscess of the maxillary teeth and its fistulizations: Multi-detector CT study

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    Aim: The aim of this study was to assess the role of MDCT and the dedicated dental software in assessment of the periapical abscesses of the maxillary teeth and in detection of abnormal fistula as well as post intervention complications.Materials and methods: This study was conducted on 20 patients with periapical abscess of the maxillary teeth. MDCT machines were used in examination of all patients. Workstation was used for manipulation of data. Dedicated dental software was used in the evaluation of all diseased teeth.Results: Fourteen patients had their abscesses involving the maxillary molar and premolar teeth, six of them showed associated oro-antral fistula (42.8%). Four patients had their abscesses surrounding the apices of the incisors, two of them showed associated oro-nasal fistula (50%). None of the patients with periapical abscesses surrounding the roots of the canine teeth (n=2) showed abnormal fistulization. Nine cases (45%) showed missing crowns and retained roots due to previous trials of extractions. Two cases (10%) of fracture of the maxillary alveolar process complicating trials of previous extraction were also encountered.Conclusion: The MDCT with its outstanding image quality of the bony structures supported by its 3-D and VR capabilities can detect the periapical dental abscess in a 3-D fashion, accurately define its location, size and extent and is excellent in evaluation of possible fistula. As compared to panorama X-ray, MDCT was more accurate in diagnosis of abnormal fistula and associated fracture of the alveolar process of the maxillary bone.KEYWORDS Periapical abscess; MDCT; Oro-antral fistula; Oro-nasal fistul

    Recent finding and new technologies in nephrolithiasis: a review of the recent literature

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    This review summarizes recent literature on advances regarding renal and ureteral calculi, with particular focus in areas of recent advances in the overall field of urolithiasis. Clinical management in everyday practice requires a complete understanding of the issues regarding metabolic evaluation and subgrouping of stone-forming patients, diagnostic procedures, effective treatment regime in acute stone colic, medical expulsive therapy, and active stone removal. In this review we focus on new perspectives in managing nephrolitihiasis and discuss recentadvances, including medical expulsive therapy, new technologies, and refinements of classical therapy such as shock wave lithotripsy, give a fundamental modification of nephrolithiasis management. Overall, this field appears to be the most promising, capable of new developments in ureterorenoscopy and percutaneous approaches. Further improvements are expected from robotic-assisted procedures, such as flexible robotics in ureterorenoscopy

    Robust endoscopic image mosaicking via fusion of multimodal estimation

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    We propose an endoscopic image mosaicking algorithm that is robust to light conditioning changes, specular reflections, and feature-less scenes. These conditions are especially common in minimally invasive surgery where the light source moves with the camera to dynamically illuminate close range scenes. This makes it difficult for a single image registration method to robustly track camera motion and then generate consistent mosaics of the expanded surgical scene across different and heterogeneous environments. Instead of relying on one specialised feature extractor or image registration method, we propose to fuse different image registration algorithms according to their uncertainties, formulating the problem as affine pose graph optimisation. This allows to combine landmarks, dense intensity registration, and learning-based approaches in a single framework. To demonstrate our application we consider deep learning-based optical flow, hand-crafted features, and intensity-based registration, however, the framework is general and could take as input other sources of motion estimation, including other sensor modalities. We validate the performance of our approach on three datasets with very different characteristics to highlighting its generalisability, demonstrating the advantages of our proposed fusion framework. While each individual registration algorithm eventually fails drastically on certain surgical scenes, the fusion approach flexibly determines which algorithms to use and in which proportion to more robustly obtain consistent mosaics
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