Deep learning-based anomaly detection in orthopedic medical imaging: A systematic literature review
Open Access
- 7 August 2025
- journal article
- review article
- Published by Elsevier in Journal of Orthopaedics
- Vol. 69, 329-345
Abstract
No abstract availableKeywords
Funding Information
- Université Claude Bernard Lyon 1
This publication has 54 references indexed in Scilit:
- Diagnosis of pes planus from X-ray images: Enhanced feature selection with deep learning and machine learning techniquesBiomedical Signal Processing and Control, 2025
- Challenges of artificial intelligence in medicine and dermatologyClinics in Dermatology, 2024
- Lower-extremity fatigue fracture detection and grading based on deep learning models of radiographsEuropean Radiology, 2022
- Ankle Fracture Detection Utilizing a Convolutional Neural Network Ensemble Implemented with a Small Sample, De Novo Training, and Multiview IncorporationJournal of Digital Imaging, 2019
- Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographsEuropean Radiology, 2019
- Detecting intertrochanteric hip fractures with orthopedist-level accuracy using a deep convolutional neural networkSkeletal Radiology, 2018
- Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic reviewComputer Methods and Programs in Biomedicine, 2018
- SLIDE: automatic spine level identification system using a deep convolutional neural networkInternational Journal of Computer Assisted Radiology and Surgery, 2017
- ISSLS PRIZE IN BIOENGINEERING SCIENCE 2017: Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention is comparable with an expert radiologistEuropean Spine Journal, 2017
- Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training DataJournal of Digital Imaging, 2017