ArticleForensic science, medicine, and pathology2022
RiFNet: Automated rib fracture detection in postmortem computed tomography.
Article in Forensic science, medicine, and pathology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Deep learning for acute rib fracture detection in CT data: a systematic review and meta-analysis.The British journal of radiology · 2024Pooled it
- Evaluating the age of rib fractures throughInternational journal of legal medicine · 2026Article
- Comment on "Automatic rib fracture detection on postmortem CT data using deep learning".International journal of legal medicine · 2026Article
- Automatic rib fracture detection on postmortem CT data using deep learning.International journal of legal medicine · 2026Article
- Diagnostic accuracy of rib fracture detection in forensic post-mortem photon counting CT.International journal of legal medicine · 2026Article
- Deep learning in rib fracture imaging: study quality assessment using the Must AI Criteria-10 (MAIC-10) checklist for artificial intelligence in medical imaging.Insights into imaging · 2025Article
- Multi-stream and multi-scale fusion rib fracture segmentation network based on UXNet.Quantitative imaging in medicine and surgery · 2025Article
- Classification of rib fracture types from postmortem computed tomography images using deep learning.Forensic science, medicine, and pathology · 2024Article
- Artificial intelligence in the practice of forensic medicine: a scoping review.International journal of legal medicine · 2024Article
- Artificial Intelligence Model Trained with Sparse Data to Detect Facial and Cranial Bone Fractures from Head CT.Journal of digital imaging · 2023Article
- An automatic fresh rib fracture detection and positioning system using deep learning.The British journal of radiology · 2023Article
- Composite Attention Residual U-Net for Rib Fracture Detection.Entropy (Basel, Switzerland) · 2023Article
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Imaging techniques are widely used for medical diagnostics. In some cases, a lack of medical practitioners who can manually analyze the images can lead to a bottleneck. Consequently, we developed a custom-made convolutional neural network (RiFNet = Rib Fracture Network) that can detect rib fractures in postmortem computed tomography. In a retrospective cohort study, we retrieved PMCT data from 195 postmortem cases with rib fractures from July 2017 to April 2018 from our database. The computed tomography data were prepared using a plugin in the commercial imaging software Syngo.via whereby the rib cage was unfolded on a single-in-plane image reformation. Out of the 195 cases, a total of 585 images were extracted and divided into two groups labeled "with" and "without" fractures. These two groups were subsequently divided into training, validation, and test datasets to assess the performance of RiFNet. In addition, we explored the possibility of applying transfer learning techniques on our dataset by choosing two independent noncommercial off-the-shelf convolutional neural network architectures (ResNet50 V2 and Inception V3) and compared the performances of those two with RiFNet. When using pre-trained convolutional neural networks, we achieved an F
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