Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …

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 …

Deep supervision, or known as' intermediate supervision'or'auxiliary supervision', is to add
supervision at hidden layers of a neural network. This technique has been increasingly …

Deep learning has played a potential role in quality healthcare with fast automated and
proper medical image analysis. In clinical applications, medical imaging is one of the most …

3D medical image segmentation methods have been successful, but their dependence on
large amounts of voxel-level annotated data is a disadvantage that needs to be addressed …

Blood vessels of the brain provide the human brain with the required nutrients and oxygen.
As a vulnerable part of the cerebral blood supply, pathology of small vessels can cause …

Malignant lesions are a huge threat to human health and have a high mortality rate. Locating
the contour of organs is a preparation step, and it helps doctors diagnose correctly …

Image registration is the process of bringing different images into a common coordinate
system—a technique widely used in various applications of computer vision, such as remote …

Background In the brain tumor magnetic resonance image (MRI) segmentation, although the
3D convolution networks (CNNs) has achieved state‐of‐the‐art results, the class and hard …

Objective. Laparoscopic renal unit-preserving resection is a routine and effective means of
treating renal tumors. Image segmentation is an essential part before tumor resection. The …