Computer-aided diagnosis (CAD) has been a promising area of research over the last two
decades. However, CAD is a very complicated subject because it involves a number of …

Background Medical image processing has a strong footprint in radio diagnosis for the
detection of diseases from the images. Several computer-aided systems were researched in …

Computed tomography (CT) imaging remains the most utilized modality for liver-related
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …

Medical image analysis requires liver segmentation for liver disease detection and
treatment. Deep learning approaches, particularly liver segmentation, have demonstrated …

The aim of this paper was to develop a region based active contour model and Fuzzy C-
Means (FCM) technique for segmentation of lung nodules. Ultimately, detection and assisted …

Purpose Liver tumor segmentation is a crucial prerequisite for computer‐aided diagnosis of
liver tumors. In the clinical diagnosis of liver tumors, radiologists usually examine multiphase …

Accurate segmentation of liver from abdominal CT scans is critical for computer‐assisted
diagnosis and therapy. Despite many years of research, automatic liver segmentation …

Abstract Computer Aided Diagnosis (CAD) systems can support physicians in classifying
different kinds of breast cancer, liver cancer and blood tumours also revealed by images …

Purpose High mortality rate due to liver cirrhosis has been reported over the globe in the
previous years. Early detection of cirrhosis may help in controlling the disease progression …

Automatic liver segmentation from abdominal images is challenging on the aspects of
segmentation accuracy, automation and robustness. There exist many methods of liver …