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Benign and malignant thyroid classification using computed tomography radiomics.

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Benign and malignant thyroid classification using computed tomography radiomics., , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)An Interpretable Classification Model Based on Characteristic Element Extraction., , and . ICMLC, page 344-349. ACM, (2019)3D thyroid segmentation in CT using self-attention convolutional neural network., , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Ultrasound multi-needle detection using deep attention U-Net with TV regularizations., , , , , , , , , and 2 other author(s). Medical Imaging: Image-Guided Procedures, volume 11598 of SPIE Proceedings, SPIE, (2021)Left ventricular myocardium segmentation in coronary computed tomography angiography using 3D deep attention u-net., , , , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 11317 of SPIE Proceedings, page 113172H. SPIE, (2020)Classification of lesion specific myocardial ischemia using cardiac computed tomography radiomics., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Automatic epicardial fat segmentation in cardiac CT imaging using 3D deep attention U-Net., , , , , , , and . Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 113132D. SPIE, (2020)Super-resolution magnetic resonance imaging reconstruction using deep attention networks., , , , , , and . Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 113132J. SPIE, (2020)