Nucleus segmentation is an imperative step in the qualitative study of imaging datasets,
considered as an intricate task in histopathology image analysis. Segmenting a nucleus is …

An accurate and automated segmentation of coronary arteries in X-ray angiograms is
essential for cardiologists to diagnose coronary artery disease in clinics. The existing deep …

Medical image segmentation plays a crucial role in diagnosing and staging diseases. It
facilitates image analysis and quantification in multiple applications, but building the right …

Deep Learning-based algorithms have shown that they are the best at segmenting,
processing, detecting, and classifying medical images. U-Net is a famous Deep Learning …

Skin cancer, particularly melanoma, has remained a severe issue for many years due to its
increasing incidences. The rising mortality rate associated with melanoma demands …

As the number of deaths from respiratory diseases due to COVID-19 and infectious diseases
increases, early diagnosis is necessary. In general, the diagnosis of diseases is based on …

Accurate segmentation of the region of interest in medical images can provide an essential
pathway for devising effective treatment plans for life-threatening diseases. It is still …

Currently, deep learning has become more and more mature in the field of medical image
segmentation. Through using the computer, the deep learning models established can …

Neural cell counting is one of the ways in which damage caused by neurodegenerative
diseases can be assessed, but it is not an easy task when it comes to neuronal counting in …

Computer-aided diagnosis is becoming increasingly important in modern medicine, and
computer-aided diagnosis systems require accurate and automatic segmentation of medical …