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Abstract #1442

Performance of different classifiers in the diagnosis of benign and malignant bone tumors based on MR diffusion kurtosis imaging

Zhizheng Zhuo1, Ying Li2, Cuiping Ren2, and Jingliang Cheng2

1Clincial Science, Philips Healthcare, Beijing, China, 2Radiology Department of First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

Recently, the AI (Artificial Intelligence) is popular in the clinical diagnosis based on medical imaging. The major target is to identify or classify the disease condition through the features extracted from the clinical images. Different algorithms (or classifiers) can be applied to classify the disease and the performance might be different for a specific clinical issue. In this work, we tried to investigate the performance of different classifiers in the diagnosis of benign and malignant bone tumors based on MRI diffusion kurtosis imaging.

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