A novel automatic segmentation method directly based on magnetic resonance imaging K-space data for auxiliary diagnosis of glioma.

"Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-946/coif). Y.X.J.W. serves as the Editor-In-Chief of Quantitative Imaging in Medicine and Surgery. D.L. serves as an unpaid editorial board member of Quantitative Imaging in Medicine and Surgery. The other authors have no conflicts of interest to declare."

"Funding: The study was partially support by the National Key Technology Research and Development Program of China ( Nos. 2023YFC3402802, 2023YFC3402800, and 2021YFF0501502 ), the Natural Science Foundation of Guangdong Province-Outstanding Youth Project ( No. 2023B1515020002 ), the Key Program for Clinical Research at Peking University Shenzhen Hospital ( No. LCYJZD2021004 ), the Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province ( No. 2023B1212060052 ), the Central Guidance for Local Science and Technology Development Project ( No. ZYYD2023D02 ), and the Guangdong Innovation Platform of Translational Research for Cerebrovascular Diseases ."