An improved YOLOv10-based framework for knee MRI lesion detection with enhanced small object recognition and low contrast feature extraction

This framework effectively connects general object detection models with the specific requirements of medical imaging, providing a precise and efficient solution for diagnosing ACL injuries in routine clinical workflows.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2026-01-20
DOI
https://doi.org/10.3389/frai.2025.1675834
Primary Topic
Knee injuries and reconstruction techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

An improved YOLOv10-based framework for knee MRI lesion detection with enhanced small object recognition and low contrast feature extraction

Hongwei Yang, ZhiAn Cai, Chuanhao Wang, Qing Zhao et al.
Frontiers in Artificial Intelligence
Knee injuries and reconstruction techniques
article

An improved YOLOv10-based framework for knee MRI lesion detection with enhanced small object recognition and low contrast feature extraction

Hongwei Yang, ZhiAn Cai, Chuanhao Wang, Qing Zhao, Luping Zhang, Tiankai Jiang, Yuyu Sun, Yuhan Sun, Wenqu Song
article en

Abstract

This framework effectively connects general object detection models with the specific requirements of medical imaging, providing a precise and efficient solution for diagnosing ACL injuries in routine clinical workflows.

Frontiers in Artificial IntelligenceVol. 8
Nantong University (CN), Affiliated Hospital of Nantong University (CN), Second People's Hospital of NanTong (CN), Wuxi Third People's Hospital (CN)
Nantong University, Bijzonder Onderzoeksfonds UGent
Openalex Percentile: Top 83%
Knee injuries and reconstruction techniques
DOIOpen Access PDFOpenAlex
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An improved YOLOv10-based framework for knee MRI lesion detection with enhanced small object recognition and low contrast feature extraction — Hongwei Yang, ZhiAn Cai, et al. · Frontiers in Artificial Intelligence (2026) | TGRS Research Map | TGRS