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Feb 1, 2019 · The model classifies the FLL medical records into positive (malignant), negative (benign) and abstaining cases.
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May 16, 2019 · The classifier evaluation was performed using the leave-one-out principle and receiver operating characteristic (ROC) curve analysis.
Method: The workflow of ROC based FLL classification includes the stages of feature extraction, statistic for building ROC curve and ROC optimal abstaining ...
A ROC optimal abstention model for FLL classification is adopted to reduce the misclassification risk and can achieve satisfied results and is effective for ...
Aug 15, 2024 · This study develops an automatic diagnosis system for liver lesions using multiphase enhanced computed tomography (CT).
Apr 22, 2017 · The FLL segmentation procedure involved wavelet multiscale analysis to extract accurate edge information and mean intensity values for ...
Jan 29, 2021 · In this paper, we propose a framework based on hierarchical convolutional neural networks (CNNs) for automatic detection and classification of focal liver ...
Dec 1, 2009 · Double-contrast MR imaging can improve diagnostic accuracy and increase confidence in characterizing focal liver lesions as HCC or metastasis.
Feb 7, 2024 · Finally, the lesion classification module aims to differentiate the detected lesions into one of the seven most common disease types (i.e., HCC, ...
Mar 21, 2018 · In this chapter, we will highlight imaging of focal liver lesions, focusing on the use of MDCT and MR imaging for disease detection and characterization.