AIMC Topic: Lumbar Vertebrae

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Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

Archives of osteoporosis
UNLABELLED: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to severe fracture using a GAM with age and three maximal vertebral body scores of fracture from a convoluti...

Estimating lumbar bone mineral density from conventional MRI and radiographs with deep learning in spine patients.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: This study aimed to develop machine learning methods to estimate bone mineral density and detect osteopenia/osteoporosis from conventional lumbar MRI (T1-weighted and T2-weighted images) and planar radiography in combination with clinical da...

Deep learning assisted segmentation of the lumbar intervertebral disc: a systematic review and meta-analysis.

Journal of orthopaedic surgery and research
BACKGROUND: In recent years, deep learning (DL) technology has been increasingly used for the diagnosis and treatment of lumbar intervertebral disc (IVD) degeneration. This study aims to evaluate the performance of DL technology for IVD segmentation ...

Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning.

Scientific reports
Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating th...

A microdiscectomy surgical video annotation framework for supervised machine learning applications.

International journal of computer assisted radiology and surgery
PURPOSE: Lumbar discectomy is among the most common spine procedures in the US, with 300,000 procedures performed each year. Like other surgical procedures, this procedure is not excluded from potential complications. This paper presents a video anno...

Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification.

Journal of imaging informatics in medicine
Large labeled data bring significant performance improvement, but acquiring labeled medical data is particularly challenging due to the laborious, time-consuming, and medically qualified annotation. Semi-supervised learning has been employed to lever...