Titlebook: Medical Image Understanding and Analysis; 24th Annual Conferen Bart?omiej W. Papie?,Ana I. L. Namburete,J. Alison Conference proceedings 20

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On New Convolutional Neural Network Based Algorithms for Selective Segmentation of Imagesations particularly in medical imaging. Robust methods can aid clinicians with diagnosis, surgical planning, etc. Many selective segmentation algorithms use geometric constraints such as information from the edges in order to determine where an object lies. It is still a challenge where there is low

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Segmentation of the Biliary Tree from MRCP Images via the Monogenic Signaligation of pancreatobiliary diseases. In current clinical practice, MRCP image interpretation remains primarily qualitative, though there is growing interest in using quantitative biomarkers, computed from segmentations of the biliary tree, to provide more objective assessments. The variable image q

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Pancreas Segmentation-Derived Biomarkers: Volume and Shape Metrics in the UK Biobank Imaging Studyst in chronic disease. Recent developments in machine learning facilitate pancreas segmentation and volume extraction. Machine learning methods could also help in designing a data-driven approach to pancreas shape characterization. We present an automated pipeline for pancreas volume and shape chara

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Localization and Identification of Lumbar Intervertebral Discs on Spine MR Images with Faster RCNN Bsame image, size and shape differences between subjects, and poor resolution. Many deep learning-based methods have been proposed recently to achieve automated detection and identification of human intervertebral discs. However, since there is usually only a small amount of labeled vertebral images

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DeepSplit: Segmentation of Microscopy Images Using Multi-task Convolutional Networkstensive improvements in semantic image segmentation. In particular, U-Net, a model specifically developed for biomedical image data, performs multi-instance segmentation through pixel-based classification. However, approaches based on U-Net tend to merge touching cells in dense cell cultures, result

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