Automated demarcation of stoke lesions from monospectral magnetic resonance imaging
scans is extremely useful for diverse research and clinical applications, including lesion …

Accurate lesion segmentation is a critical technology basis for the treatment and prognosis
of stroke. Stroke lesion segmentation suffers from complex background and noise interferes …

There are considerable interests in automatic stroke lesion segmentation on magnetic
resonance (MR) images in the medical imaging field, as stroke is an important …

Biometric measurements in fetal ultrasound images are one of the most highly demanding
medical image analysis tasks that can directly contribute to diagnosing fetal diseases …

Brain segmentation of stroke patients can facilitate brain modeling for electrical non-invasive
brain stimulation, a therapy for stimulating brain function using an electric current. However …

Vision transformer architectures attract widespread interest due to their robust
representation capabilities of global features. Transformer-based methods as the encoder …

Intracerebral hemorrhage (ICH) is a serious category of head injury, which means bleeding
occurs inside the skull, and in many cases leads to a high disability or mortality. Therefore …

Accurate stroke segmentation is a crucial task in establishing a computer-aided diagnostic
system for brain diseases. However, reducing false negatives and accurately segmenting …

A supervised deep learning network like the UNet has performed well in segmenting brain
anomalies such as lesions and tumours. However, such methods were proposed to perform …

Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal
cancer (CRC) in clinical practice. However, due to scale variation and blurry polyp …