Computer-aided liver diagnosis helps doctors accurately identify liver abnormalities and
reduce the risk of liver surgery. Early diagnosis and detection of liver lesions depend mainly …

Automatic liver tumor segmentation would have a big impact on liver therapy planning
procedures and follow-up assessment, thanks to standardization and incorporation of full …

Simple Summary As a primary hepatic tumor, hepatocellular carcinoma (HCC) is the most
prevalent kind. Recent developments in magnetic resonance imaging (MRI) and computed …

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

Liver tumor segmentation from CT images plays an important role in disease diagnosis and
treatment planning. In this paper, we propose an automatic segmentation framework …

We use the k-core decomposition to visualize large scale complex networks in two
dimensions. This decomposition, based on a recursive pruning of the least connected …

Liver tumor segmentation plays an essential role in diagnosis and treatment of
hepatocellular carcinoma or metastasis. However, accurate and automatic tumor …

Purpose The intensity profile of an image in the vicinity of a tissue's boundary is modeled by
a step/ramp function. However, this assumption does not hold in cases of low-contrast …

Human disease identification from the scanned body parts helps medical practitioners make
the right decision in lesser time. Image segmentation plays a vital role in automated …

Objective. Our objective is to develop a computerized scheme for liver tumor segmentation
in MR images. Materials and Methods. Our proposed scheme consists of four main stages …