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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| Main Authors: | Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11006069/ |
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