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Chapter and Conference Paper
AugPaste: One-Shot Anomaly Detection for Medical Images
Due to the high cost of manually annotating medical images, especially for large-scale datasets, anomaly detection has been explored through training models with only normal data. Lacking prior knowledge of tr...
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Chapter and Conference Paper
Survival Prediction of Glioma Tumors Using Feature Selection and Linear Regression
Early diagnosis of brain tumor is crucial for treatment planning. Quantitative analyses of segmentation can provide information for tumor survival prediction. The effectiveness of convolutional neural network ...
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Chapter and Conference Paper
Utility of Brain Parcellation in Enhancing Brain Tumor Segmentation and Survival Prediction
In this paper, we proposed a UNet-based brain tumor segmentation method and a linear model-based survival prediction method. The effectiveness of UNet has been validated in automatically segmenting brain tumor...