Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography

Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography

The automatic segmentation of liver tumors plays an important role in the diagnosis and treatment of liver cancer. While deep convolutional neural network (DCNN) models are widely used for segmentation tasks in medical imaging, they require 1,000 to 10,000 annotated cases for effective training. How...

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Bibliographic Details
Main Authors: Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
deep learning
liver tumor segmentation
medical image analysis
small-data AI
Online Access:https://ieeexplore.ieee.org/document/11006069/
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https://ieeexplore.ieee.org/document/11006069/

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