Aug 2026· Oral Radiology/Springer· Vol 42, pp. 1192 - 1205· 0 citations· 32 references
Medicine
TL;DR
This study demonstrates the feasibility of a segmentation-first, classification-second deep learning pipeline for automated MRI-based TMJ-OA detection, providing a methodological foundation for future multi-institutional validation of a radiation-free diagnostic approach to TMJ-OA.
We compared single-modality models, intra-modality ensembles, and selective cone-beam computed tomography (CBCT)–magnetic resonance imaging (MRI) fusion for diagnosing temporomandibular joint osteoarthritis (TMJ-OA). This single-center retrospective cohort included 1598 patients (1118 females and 480 males; mean age ± ...
3D-CNNs trained with vertebra-level labels can accurately and reliably classify vertebral metastatic lesion quality from CT scans, offering a scalable path toward automated characterization of metastatic spine disease to support clinical decision-making and large-scale radiomics research.
V. Hong, A. Bulent, N. Haouchine et al.· medRxiv· 0 citations
Proper diagnosis and segmentation of periapical lesions using Cone Beam Computed Tomography (CBCT) imaging play an important role in determining the best possible strategy for treatment of such pathologies. Even though CBCT provides a better three-dimensional visualization than regular two-dimensional X-ray images, mul...
Sarmad M. Hamozi· Journal of Health and Biolog...· 0 citations
A dual-stream, transformer-enhanced multimodal (panoramic radiography + selected CBCT slices) deep learning framework designed as a clinician-in-the-loop system aimed at reducing diagnostic variability in complex boundary cases where visual interpretation alone may be subjective.
The observed differences among detection architectures and inference configurations provide a foundation for developing more accurate AI-assisted detection systems, although clinical examination remains essential for determining lesion activity, cavitation status, and treatment decisions.
M. Baraka, Abdallah Elsayed, Ahmed Issa et al.· E -journal of dentistry· 0 citations
RATIONALE AND OBJECTIVES
The study aimed to develop and validate a deep learning (DL) model based on X-ray and computed tomography (CT) to diagnose acute vertebral fractures (VFs), and to compare its diagnostic accuracy against spine surgeons.
MATERIALS AND METHODS
This single-center, retrospective diagnostic accurac...
Yong-Xin Chen, Hao Hu, Zhuang-Hui Wang et al.· Academic Radiology· 0 citations
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