Liver segmentation is critical for the location and diagnosis of liver cancer. The variant of U-
Net network with skip connections has become popular in the medical image segmentation …

The liver is one of the organs with the highest incidence rate in the human body, and late-
stage liver cancer is basically incurable. Therefore, early diagnosis and lesion location of …

Purpose: This paper proposes a new network framework called EAR-U-Net, which
leverages EfficientNetB4, attention gate, and residual learning techniques to achieve …

Objectives Accurate automatic liver segmentation has important value for subsequent tumor
segmentation, diagnosis, and treatment. In this paper, a Multiscale Cascaded Feature …

Background and objective Liver segmentation is an essential prerequisite for liver cancer
diagnosis and surgical planning. Traditionally, liver contour is delineated manually by …

Background The liver is an important organ that undertakes the metabolic function of the
human body. Liver cancer has become one of the cancers with the highest mortality. In …

Liver segmentation is a critical step in liver cancer diagnosis and surgical planning. The U-
Net's architecture is one of the most efficient deep networks for medical image segmentation …

Automatic segmentation of the liver in abdominal CT images is critical for guiding liver
cancer biopsies and treatment planning. Yet, automatic segmentation of CT liver images …

Liver cancer is one of the leading causes of cancer death. Accurate and automatic liver
tumor segmentation methods are urgent needs in clinical practice. Currently, Fully …

Automatic assessing the location and extent of liver and liver tumor is critical for radiologists,
diagnosis and the clinical process. In recent years, a large number of variants of U-Net …