Prostate cancer is the second most diagnosed cancer of men all over the world. In the last
few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have …

Medical image acquisition devices provide a vast amount of anatomical and functional
information, which facilitate and improve diagnosis and patient treatment, especially when …

Image segmentation is an important task in many medical applications. Methods based on
convolutional neural networks attain state-of-the-art accuracy; however, they typically rely on …

Robot warehouse automation has attracted significant interest in recent years, perhaps most
visibly in the Amazon Picking Challenge (APC)[1]. A fully autonomous warehouse pick-and …

It is often a difficult task to accurately segment images with intensity inhomogeneity, because
most of representative algorithms are region-based that depend on intensity homogeneity of …

Background: Alzheimer's is a degenerative dementing disorder that starts with a mild
memory impairment and progresses to a total loss of mental and physical faculties. The …

The large spatial inhomogeneity in transmit B1 field (B1+) observable in human MR images
at high static magnetic fields (B0) severely impairs image quality. To overcome this effect in …

A probabilistic framework is presented that enables image registration, tissue classification,
and bias correction to be combined within the same generative model. A derivation of a log …

Abstract The Open Access Series of Imaging Studies is a series of magnetic resonance
imaging data sets that is publicly available for study and analysis. The initial data set …

Characterizing the performance of image segmentation approaches has been a persistent
challenge. Performance analysis is important since segmentation algorithms often have …