Brain is an amazing organ that controls all activities of a human. Any abnormality in the
shape of anatomical regions of the brain needs to be detected as early as possible to reduce …

The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark
(LiTS), which was organized in conjunction with the IEEE International Symposium on …

U-Nets are a go-to neural architecture across numerous tasks for continuous signals on a
square such as images and Partial Differential Equations (PDE), however their design and …

Recently, deep learning has unlocked unprecedented success in various domains,
especially using images, text, and speech. However, deep learning is only beneficial if the …

Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin
is of key importance in many neurological research studies. Currently, measurements are …

Abstract The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of
multiple open-source software libraries which house top-performing algorithms used …

There is significant interest in the development and application of deep neural networks
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …

Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for
academic and industry researchers and graduate students taking courses on machine …

We propose a novel semi-supervised image segmentation method that simultaneously
optimizes a supervised segmentation and an unsupervised reconstruction objectives. The …