Radiomics in liver diseases: Current progress and future opportunities
J Wei, H Jiang, D Gu, M Niu, F Fu, Y Han… - Liver …, 2020 - Wiley Online Library
Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have
become an increasingly significant health problem worldwide. Noninvasive imaging plays a …
become an increasingly significant health problem worldwide. Noninvasive imaging plays a …
Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields
Automatic segmentation of the liver and its lesion is an important step towards deriving
quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support …
quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support …
Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks
Automatic segmentation of the liver and hepatic lesions is an important step towards
deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision …
deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision …
[HTML][HTML] Radiomics in hepatocellular carcinoma: A state-of-the-art review
S Yao, Z Ye, Y Wei, HY Jiang… - World Journal of …, 2021 - ncbi.nlm.nih.gov
Hepatocellular carcinoma (HCC) is the most common cancer and the second major
contributor to cancer-related mortality. Radiomics, a burgeoning technology that can provide …
contributor to cancer-related mortality. Radiomics, a burgeoning technology that can provide …
Ahcnet: An application of attention mechanism and hybrid connection for liver tumor segmentation in ct volumes
H Jiang, T Shi, Z Bai, L Huang - Ieee Access, 2019 - ieeexplore.ieee.org
The liver is a common site for the development of primary (ie, originating from the liver, eg,
hepatocellular carcinoma) or secondary (ie, spread to the liver, eg, colorectal cancer) tumor …
hepatocellular carcinoma) or secondary (ie, spread to the liver, eg, colorectal cancer) tumor …
Bottleneck feature supervised U-Net for pixel-wise liver and tumor segmentation
LI Song, KF Geoffrey, HE Kaijian - Expert Systems with Applications, 2020 - Elsevier
Liver cancer is one of the most common cancer types with high death rate. Doctors diagnose
cancer by examining the CT images, which can be time-consuming and prone to error …
cancer by examining the CT images, which can be time-consuming and prone to error …
Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
Computed tomography (CT) imaging remains the most utilized modality for liver-related
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …
Tumor burden analysis on computed tomography by automated liver and tumor segmentation
MG Linguraru, WJ Richbourg, J Liu… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
The paper presents the automated computation of hepatic tumor burden from abdominal
computed tomography (CT) images of diseased populations with images with inconsistent …
computed tomography (CT) images of diseased populations with images with inconsistent …
Deep learning initialized and gradient enhanced level-set based segmentation for liver tumor from CT images
Liver and liver tumor segmentation provides vital biomarkers for surgical planning and
hepatic diagnosis. In this paper, we propose and validate a novel level-set method …
hepatic diagnosis. In this paper, we propose and validate a novel level-set method …
Adaptive local window for level set segmentation of CT and MRI liver lesions
We propose a novel method, the adaptive local window, for improving level set
segmentation technique. The window is estimated separately for each contour point, over …
segmentation technique. The window is estimated separately for each contour point, over …