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Effect of observer variability and training cases on U-Net segmentation performance.

, , , , , , и . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, том 11316 из SPIE Proceedings, стр. 113160T. SPIE, (2020)

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Rowena Lanfermann

Marcus Yip

Ching Man Yip

Alexander Yip

Rowena Arzt

 

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Cascade of U-Nets in the detection and classification of coronary artery calcium in thoracic low-dose CT., , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 11314 из SPIE Proceedings, SPIE, (2020)Detection and classification of coronary artery calcifications in low dose thoracic CT using deep learning., , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 10950 из SPIE Proceedings, стр. 1095039. SPIE, (2019)Effect of observer variability and training cases on U-Net segmentation performance., , , , , , и . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, том 11316 из SPIE Proceedings, стр. 113160T. SPIE, (2020)Radiomic texture analysis for the assessment of osteoporosis on low-dose thoracic CT scans., , , , , , , , , и 1 other автор(ы). Medical Imaging: Computer-Aided Diagnosis, том 11597 из SPIE Proceedings, SPIE, (2021)