相关实验视频

Updated: Jan 6, 2026

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
08:39

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

518

基于CT图像的YOLOv12算法辅助检测和分类侧向小骨突破和亚骨骨基:多中心研究:多中心研究

Jiayi Liu1, Peng Sun2, Yousheng Yuan1

  • 1Department of Radiology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China.

JMIR medical informatics
|September 9, 2025
PubMed
概括

一个深层卷积神经网络 (DCNN),YOLOv12,在CT扫描上有效地区分了侧面骨突起骨折 (LMAF) 和亚骨骨 (SFOs). 这种人工智能模型显著优于仅使用CT的放射科医生,在这些具有挑战性的诊断中接近基于MRI的准确性.

关键词:
在这里,我们可以看到AIAIAI.这就是为什么CTCTCTCTCTCT电脑断层扫描X射线扫描人工智能的人工智能是人工智能.这是分类分类的分类.深度卷积神经网络是一个深度卷积神经网络.侧面状骨突破 骨折 侧面状骨突破副支柱骨的骨头.

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