MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation.

Photoplethysmography and its application in clinical physiological measurement

Follow up what we will offer in this article about philosophical transactions of the royal society of london series b biological sciences no 600 vol 233 studies of the post glacial history of british vegetation x correlation between climate forest composition prehistoric agriculture and peat st. You know really that this book is coming as the best seller book today. So, when you are really a good reader or you're fans of the author, it does will be funny if you don't have this book. It means that you have to get this book. For you who are starting to learn about something new and feel curious about this book, it's easy then. Just get this book and feel how this book will give you more exciting lessons.

Philosophical Transactions of the Royal Society of London. for the Year Mdcccxxvii. Part I. Volume Cxvii:355–388, 1827

A new statistic has been developed to quantify the amount of regularity in data. This statistic, ApEn (approximate entropy), appears to have potential application throughout medicine, notably in electrocardiogram and related heart rate data analyses and in the analysis of endocrine hormone release pulsatility. The focus of this article is ApEn. We commence with a simple example of what we are trying to discern. We then discuss exact regularity statistics and practical difficulties of using them in data analysis. The mathematic formula development for ApEn concludes the Solution section. We next discuss the two key input requirements, followed by an account of a pilot study successfully applying ApEn to neonatal heart rate analysis. We conclude with the important topic of ApEn as a relative (not absolute) measure, potential applications, and some caveats about appropriate usage of ApEn. Appendix A provides example ApEn and entropy computations to develop intuition about these measures. Appendix B contains a Fortran program for computing ApEn. This article can be read from at least three viewpoints. The practitioner who wishes to use a "black box" to measure regularity should concentrate on the exact formula, choices for the two input variables, potential applications, and caveats about appropriate usage. The physician who wishes to apply ApEn to heart rate analysis should particularly note the pilot study discussion. The more mathematically inclined reader will benefit from discussions of the relative (comparative) property of ApEn and from Appendix A.

A regularity statistic for medical data analysis

Objective The effect of colonoscopy on colorectal cancer mortality is limited by several factors, among them a certain miss rate, leading to limited adenoma detection rates (ADRs). We investigated the effect of an automatic polyp detection system based on deep learning on polyp detection rate and ADR. Design In an open, non-blinded trial, consecutive patients were prospectively randomised to undergo diagnostic colonoscopy with or without assistance of a real-time automatic polyp detection system providing a simultaneous visual notice and sound alarm on polyp detection. The primary outcome was ADR. Results Of 1058 patients included, 536 were randomised to standard colonoscopy, and 522 were randomised to colonoscopy with computer-aided diagnosis. The artificial intelligence (AI) system significantly increased ADR (29.1%vs20.3%, p Conclusions In a low prevalent ADR population, an automatic polyp detection system during colonoscopy resulted in a significant increase in the number of diminutive adenomas detected, as well as an increase in the rate of hyperplastic polyps. The cost–benefit ratio of such effects has to be determined further. Trial registration number ChiCTR-DDD-17012221; Results.

https://gut.bmj.com/content/gutjnl/68/10/1813.full.pdf

Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study.

Examination of the whole gastrointestinal tract represents a challenge for endoscopists due to its length and inaccessibility using natural orifices. Moreover, radiologic techniques are relatively insensitive for diminutive, flat, infiltrative, or inflammatory lesions of the small bowel. Since 1994, video capsules (VCEs) have been developed to allow direct examination of this inaccessible part of the gastrointestinal tract and to help doctors to find the cause of symptoms such as stomach pain, disease of Crohn, diarrhoea, weight loss, rectal bleeding, and anaemia. The Pillcam© video capsule designed by Given Imaging Company is the most popular of them. This autonomous embedded system allows acquiring about fifty thousand images of gastrointestinal tract during more than twelve hours of an analysis. However, acquired images are of low resolution and imaging conditions could be very poor as the movements and the speed of the VCE as illumination are not entirely controlled all along the transit of the capsule through the whole gastrointestinal tract. As a consequence segmentation of VCE images is a real challenging problem: first of all specialists need a flexible segmentation tool that makes delineations of very different structures (polyps, metastasis... to name a few) possible and second, the proposed method should be efficient even in difficult imaging conditions. In this article, an adapted segmentation method based on statistical active contours for VCE segmentation is proposed and tested on various types of gastrointestinal structures.

Segmentation of video capsule endoscopic images using alpha-divergence based active contour method

It is progressively realized that noise can play a constructive role in the domain of nonlinear information processing. This phenomenon, also known as stochastic resonance (SR) effect, has experienced large varieties of extensions with variations concerning the type of noise, the type of information carrying signal or the type of nonlinear system interacting with the signal-noise mixture. In this article, we propose an interpretation for the mechanism of noise-enhanced image restoration with nonlinear PDE (Partial Differential Equation) recently demonstrated in literature. More precisely, a link is established between the action of noise in a nonlinear Perona-Malik anisotropic diffusion and stochastic resonance in memoryless nonlinear systems for 1-D signals. For illustration some preliminary results are presented on classical "cameraman" image and the inner of SR mechanism is theoretically and practically studied using a simple set of parameters regarding the PDE used and the modeling of boundaries within images.

/pdf/useful-noise-effect-for-nonlinear-pde-based-restoration-of-os9tfkimso.pdf

Useful Noise effect for nonlinear PDE based restoration of scalar images

Purpose Image segmentation of MRI data is a challenging problem due to the specificity of the acquisition process and more precisely to the particularity of the associated corrupting noise that can be modeled by a Rician distribution. This particular distribution leads to multimodal area within MR image where foreground and target organs are characterized by different probability density functions (pdf) (mainly Rayleigh distribution and Gaussian distribution). Due to this particularity, classical automatic segmentation technique like Chan-Vese often failed in obtaining satisfying results of delineations in MR images where pdf of organs could overlap with background. This is the case for example in MR prostate image analysis, where bladder, prostate, and rectum can be hardly segmented thanks to classical approaches. Method In the framework of active contour segmentation [2], we propose to evaluate for MRI segmentation performances of histogram based method [1,3]. Main idea of this approach is to define, in a variationnal framework of region based active contours segmentation, evolution criteria accounting for the distances between probability density functions (pdf) of the inner and outer regions of the active contour and given pdfs of reference of objects and background. To achieve the performances evaluation, first a statistical study of the accuracy of the technique is proposed on synthetic MR data for different levels of corrupting noise and for different distance criteria between two given pdf and, second, a prospective study made on prostate MRI is shown for bladder, prostate and rectum segmentation, which respective delineation is of primary interest in the radiotherapy treatment of prostatic adenocarcinoma. Results A statistical study performed on synthetic MR images shows that histogram based active contour method outperform classical approach like the Chan-Vese one in terms of accuracy and that depending on the distance criterion selected, an adaptation to the level of corrupting noise is possible to reach the best accuracy possible. The prospective study made on prostate MRI shows that the proposed approach suits well to the particular MR distribution function: mainly, bladder, prostate and rectum segmentation are better performed by the proposed approach than with more classical active contour approaches.

Aymeric Histace

Papers

Segmentation of video capsule endoscopic images using alpha-divergence based active contour method

Useful Noise effect for nonlinear PDE based restoration of scalar images

MRI segmentation using histogram based active contour method: application to prostate MR image analysis

Tagged MR cardiac images analysis

Analyse d'images IRM cardiaques marquées