Over the past few years, the rapid development of deep learning technologies for computer
vision has significantly improved the performance of medical image segmentation …

Accurate segmentation of the fetal head and pubic symphysis in intrapartum ultrasound
images and measurement of fetal angle of progression (AoP) are critical to both outcome …

Liver ultrasound is widely used in clinical practice due to its advantages of non-
invasiveness, non-radiation, and real-time imaging. Accurate segmentation of the liver …

Nuclei segmentation is a fundamental prerequisite in the digital pathology workflow. The
development of automated methods for nuclei segmentation enables quantitative analysis of …

Medical image segmentation has made significant progress in recent years. Deep learning-
based methods are recognized as data-hungry techniques, requiring large amounts of data …

Accurate segmentation of lesion based on the Dermatoscopy images and Colonoscopy
polyp images is beneficial for subsequent diagnosis and treatment. Although effectiveness …

Excellent performance has been demonstrated by convolutional neural network (CNN) in
salient object detection for optical remote sensing images (ORSI-SOD). However, the …

Computer-aided diagnosis has been slow to develop in the field of oral ulcers. One of the
major reasons for this is the lack of publicly available datasets. However, oral ulcers have …

Accurate segmentation of the tumor area is crucial for the treatment and prognosis of
patients with bladder cancer. Cystoscopy is the gold standard for diagnosing bladder …

Medical image segmentation aims to locate lesions within a given image to assist doctors in
diagnosis and treatment, playing a crucial role in improving patient outcomes. Recently, the …