Fine renal artery segmentation on abdominal CT angiography (CTA) image is one of the
most important tasks for kidney disease diagnosis and pre-operative planning. It will help …

Abstract Three-dimensional (3D) integrated renal structures (IRS) segmentation targets
segmenting the kidneys, renal tumors, arteries, and veins in one inference. Clinicians will …

Semantic image segmentation plays an important role in modeling patient-specific anatomy.
We propose a convolution neural network, called Kid-Net, along with a training schema to …

Deep neural networks often suffer from performance inconsistency for multiorgan
segmentation in medical images; some organs are segmented far worse than others. The …

Abstract 3D fine renal artery segmentation on abdominal CTA image targets on the
segmentation of the complete renal artery tree which will help clinicians locate the interlobar …

Renal tubular structures, such as ureters, arteries and veins, are very important for building a
complete digital 3D anatomical model of a patient. However, they can be challenging to …

Accurate segmentation of the renal cancer structure, including the kidney, renal tumors,
veins, and arteries, has great clinical significance, which can assist clinicians in diagnosing …

Retrieval networks are essential for searching and indexing. Compared to classification
networks, attention visualization for retrieval networks is hardly studied. We formulate …

Renal artery segmentation plays a fundamental role in nephrectomy, which can help
surgeons get a better under-standing of vascular structures. However, the similar intensity …

Renal compartment segmentation on CT images targets on extracting the 3D structure of
renal compartments from abdominal CTA images and is of great significance to the …