Journal of magnetic resonance imaging : JMRI
Apr 27, 2024
BACKGROUND: Methods for grading and localization of lumbar disc herniation (LDH) on MRI are complex, time-consuming, and subjective. Utilizing deep learning (DL) models as assistance would mitigate such complexities.
Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for osteoporosis, it is expensive and not widely available. In contrast, kidney-ureter-bla...
Journal of imaging informatics in medicine
Apr 18, 2024
We aimed to develop and validate a deep convolutional neural network (DCNN) model capable of accurately identifying spondylolysis or spondylolisthesis on lateral or dynamic X-ray images. A total of 2449 lumbar lateral and dynamic X-ray images were co...
BACKGROUND: Diagnosing early lumbar spondylolisthesis is challenging for many doctors because of the lack of obvious symptoms. Using deep learning (DL) models to improve the accuracy of X-ray diagnoses can effectively reduce missed and misdiagnoses i...
Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
Apr 3, 2024
BACKGROUND: 'Mo-fi-disc' is a new scoring system that quantifies degeneration of the lumbar spine and predicts the intensity of low back pain (LBP). However, its association with LBP-related disability is unknown. In the present study, we aimed to an...
PURPOSE: High quality scan prescription that optimally covers the area of interest with scan planes aligned to relevant anatomical structures is crucial for error-free radiologic interpretation. The goal of this project was to develop a machine learn...
Robot-assisted pedicle screw placement is prone to guide wire migration, and the related influencing factors have not yet been discussed. Therefore, this study aimed to investigate and analyze the causes of robot-assisted spinal pedicle guide wire di...
OBJECTIVE: Achieving appropriate spinopelvic alignment has been shown to be associated with improved clinical symptoms. However, measurement of spinopelvic radiographic parameters is time-intensive and interobserver reliability is a concern. Automate...
Journal of orthopaedic surgery and research
Mar 25, 2024
PURPOSE: An efficient physics-informed deep learning approach for extracting spinopelvic measures from X-ray images is introduced and its performance is evaluated against manual annotations.
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