Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis
and vessel segmentation. This paper presents a survey of techniques and algorithms for …

Abstract Malignant Focal Liver Lesion (FLL) is a main cause of primary liver cancer. In most
existing Computer-Aided Diagnosis (CAD) systems of FLLs, machine learning and data …

Background Proper segmentation of the liver from medical images is critical for computer-
assisted diagnosis, therapy and surgical planning. Knowledge of its vascular structure …

The earliest and most accurate detection of the pathological manifestations of hepatic
diseases ensures effective treatments and thus positive prognostic outcomes. In clinical …

This paper presents an automatic Couinaud segmentation method based on deep learning
of key point detection. Assuming that the liver mask has been extracted, the proposed …

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 …

Background Recent reports have shown the potential for deep learning (DL) models to
automatically segment of Couinaud liver segments and future liver remnant (FLR) for liver …

Successful liver resection relies on accurate estimation of future liver remnant volume
(FLRV). According to Couinaud's scheme, a liver is composed of eight functionally …

Purpose The accurate delineation of hepatic vessels is important to diagnosis and treatment
planning. To improve the segmentation of these vessels and extract small structures, we …

Abstract Background and Objective Automatic functional region annotation of liver should be
very useful for preoperative planning of liver resection in the clinical domain. However, many …