Stereo matching algorithms usually consist of four steps, including matching cost calculation,
matching cost aggregation, disparity calculation, and disparity refinement. Existing CNN …

We aim at segmenting small organs (eg, the pancreas) from abdominal CT scans. As the
target often occupies a relatively small region in the input image, deep neural networks can …

It is becoming increasingly clear that mitochondria play an important role in neural function.
Recent studies show mitochondrial morphology to be crucial to cellular physiology and …

MR imaging is a promising noninvasive modality that can provide a comprehensive picture
of renal anatomy and function in a single examination. The advantages of MR imaging are …

Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic
procedures for early detection and diagnosis are crucial. Some difficulties with manual …

The methodology presented in the first edition was considered established practice or
settled science in the medical image analysis community in 2010–2011. Progress in this …

As a preprocessing step, image segmentation, which can do partition of an image into
different regions, plays an important role in computer vision, objects recognition, tracking …

Human disease identification from the scanned body parts helps medical practitioners make
the right decision in lesser time. Image segmentation plays a vital role in automated …

Introduction Kidney tumors are common cancer in advanced age, and providing early
detection is crucial. Medical imaging and deep learning methods are increasingly attractive …

We aim at segmenting a wide variety of organs, including tiny targets (eg, adrenal gland),
and neoplasms (eg, pancreatic cyst), from abdominal CT scans. This is a challenging task in …