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 …
[HTML][HTML] Automated machine learning for differentiation of hepatocellular carcinoma from intrahepatic cholangiocarcinoma on multiphasic MRI
With modern management of primary liver cancer shifting towards non-invasive diagnostics,
accurate tumor classification on medical imaging is increasingly critical for disease …
accurate tumor classification on medical imaging is increasingly critical for disease …
Segmentation of liver tumors on CT images
D Pescia - 2011 - theses.hal.science
This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of
great clinical interest since it allows physicians benefiting from reproducible and reliable …
great clinical interest since it allows physicians benefiting from reproducible and reliable …
Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning
Abstract Purpose Liver Imaging Reporting and Data System (LI-RADS) uses multiphasic
contrast-enhanced imaging for hepatocellular carcinoma (HCC) diagnosis. The goal of this …
contrast-enhanced imaging for hepatocellular carcinoma (HCC) diagnosis. The goal of this …
Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies
Radiological longitudinal follow-up of tumors in CT scans is essential for disease
assessment and liver tumor therapy. Currently, most tumor size measurements follow the …
assessment and liver tumor therapy. Currently, most tumor size measurements follow the …
[HTML][HTML] Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring
Segmentation of liver tumors from Computed Tomography (CT) and tumor burden analysis
play an important role in the choice of therapeutic strategies for liver diseases and treatment …
play an important role in the choice of therapeutic strategies for liver diseases and treatment …
Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CF s), convolutional neural networks …
Purpose As part of a program to implement automatic lesion detection methods for whole
body magnetic resonance imaging (MRI) in oncology, we have developed, evaluated, and …
body magnetic resonance imaging (MRI) in oncology, we have developed, evaluated, and …
Automatic liver segmentation in MRI images using an iterative watershed algorithm and artificial neural network
H Masoumi, A Behrad, MA Pourmina… - … signal processing and …, 2012 - Elsevier
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 …
the computer-aided diagnosis of liver pathology. The first and essential step for diagnosis is …
[HTML][HTML] Artificial Intelligence, Machine Learning, and Deep Learning in the Diagnosis and Management of Hepatocellular Carcinoma
C Larrain, A Torres-Hernandez, DB Hewitt - Livers, 2024 - mdpi.com
Artificial Intelligence (AI) can be a useful tool in the management of disease processes such
as hepatocellular carcinoma (HCC) as treatment decisions are often complex and …
as hepatocellular carcinoma (HCC) as treatment decisions are often complex and …