Efficient urinary stone type prediction: a novel approach based on self-distillation

Efficient urinary stone type prediction: a novel approach based on self-distillation

Abstract Urolithiasis is a leading urological disorder where accurate preoperative identification of stone types is critical for effective treatment. Deep learning has shown promise in classifying urolithiasis from CT images, yet faces challenges with model size and computational efficiency in real...

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Bibliographic Details
Main Authors: Kun Liu, Xuanqi Zhang, Haiyun Yu, Jie Song, Tianxiao Xu, Min Li, Chang Liu, Shuang Liu, Yucheng Wang, Zhenyu Cui, Kun Yang
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Urolithiasis
Computerized tomography
Self-distillation
Deep learning
Preoperative diagnosis
Online Access:https://doi.org/10.1038/s41598-024-73923-6
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https://doi.org/10.1038/s41598-024-73923-6

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