The objective of human pose estimation (HPE) derived from deep learning aims to
accurately estimate and predict the human body posture in images or videos via the …

Cell segmentation is the most significant task in microscopic image analysis as it facilitates
differential cell counting and analysis of sub-cellular structures for diagnosing …

Medical image segmentation aims at recognizing the object of interest from surrounding
tissues and structures, which is essential for the reliable diagnosis and morphological …

Accurate fault identification provides an important basis for well location deployment, oil and
gas resource development. However, obtaining a large number of fault samples through …

Objective. Deep learning networks such as convolutional neural networks (CNN) and
Transformer have shown excellent performance on the task of medical image segmentation …

Background: Dermoscopic image segmentation using deep learning algorithms is a critical
technology for skin cancer detection and therapy. Specifically, this technology is a spatially …

Objective: Precise segmentation of breast ultrasound images is essential for early breast
cancer screening. Convolutional neural networks (CNNs) have made great progress in …

Abstract Type-B Aortic Dissection is a rare but fatal cardiovascular disease characterized by
a tear in the inner layer of the aorta, affecting 3.5 per 100,000 individuals annually. In this …

The precise prostate gland and prostate cancer (PCa) segmentations enable the fusion of
magnetic resonance imaging (MRI) and ultrasound imaging (US) to guide robotic prostate …

Accurate segmentation of CT images is crucial for clinical diagnosis and preoperative
evaluation of robotic surgery, but challenges arise from fuzzy boundaries and small-sized …