In biomedical image analysis, information about the location and appearance of tumors and
lesions is indispensable to aid doctors in treating and identifying the severity of diseases …

Focal cortical dysplasias (FCDs) are malformations of cortical development and one of the
most common pathologies causing pharmacoresistant focal epilepsy. Resective …

Computer-aided medical image analysis plays a significant role in assisting medical
practitioners for expert clinical diagnosis and deciding the optimal treatment plan. At present …

This paper introduces a comprehensive approach for segmenting regions of interest (ROI) in
diverse medical imaging datasets, encompassing ultrasound, CT scans, and X-ray images …

Background and Objective To test the hypothesis that a multicenter-validated computer deep
learning algorithm detects MRI-negative focal cortical dysplasia (FCD). Methods We used …

The U-Net has achieved great success in medical image segmentation. Most U-Nets follow
the encoding–decoding-decision inference path and propagate the features from encoding …

The precise segmentation of surgical instruments is the key link for the stable and
reasonable operation of surgical robots. However, accurate surgical instrument …

Medical image segmentation has attracted increasing attention due to its practical clinical
requirements. However, the prevalence of small targets still poses great challenges for …

Objective: He morrhagic stroke is a leading threat to human's health. The fast-developing
microwave-induced thermoacoustic tomography (MITAT) technique holds potential to do …

Automatic liver tumor segmentation is a paramount important application for liver tumor
diagnosis and treatment planning. However, it has become a highly challenging task due to …