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 …

Liver and tumor segmentation plays an important role for many liver interventions.
Automation of segmentation steps will bring a substantial improvement to clinical workflows …

This paper presents an automatic liver segmentation algorithm based on fast marching and
improved fuzzy cluster methods, which can segment liver from abdominal MR images …

Precise liver segmentation in abdominal MRI images is one of the most important steps for
the computer-aided diagnosis of liver pathology. The first and essential step for diagnosis is …

Developing a robust method for liver segmentation from magnetic resonance images is a
challenging task because of the similar intensity values between adjacent organs, the …

Purpose: Liver segmentation is a fundamental step in computer‐aided liver disease
diagnosis and surgery planning. For the sake of high accuracy and efficiency, in this study …

A 68-year-old woman with a history of hepatocellular carcinoma underwent conventional
transarterial chemoembolization. Manual tumor segmentation on images, which can be …

Recently a growing interest has been seen in minimally invasive treatments with open
configuration magnetic resonance (Open-MR) scanners. Because of the lower magnetic …

Objective To assess the performance of convolutional neural networks (CNNs) for
semiautomated segmentation of hepatocellular carcinoma (HCC) tumors on MRI. Methods …

Objective We aim to develop and validate a three-dimensional convolutional neural network
(3D-CNN) model for automatic liver segment segmentation on MRI images. Methods This …