AIMC Topic: Bone Remodeling

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Fully automated evaluation of condylar remodeling after orthognathic surgery in skeletal class II patients using deep learning and landmarks.

Journal of dentistry
OBJECTIVE: Condylar remodeling is a key prognostic indicator in maxillofacial surgery for skeletal class II patients. This study aimed to develop and validate a fully automated method leveraging landmark-guided segmentation and registration for effic...

Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients.

Orthodontics & craniofacial research
OBJECTIVE: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analysed with ...

Preliminary study on AI-assisted diagnosis of bone remodeling in chronic maxillary sinusitis.

BMC medical imaging
OBJECTIVE: To construct the deep learning convolution neural network (CNN) model and machine learning support vector machine (SVM) model of bone remodeling of chronic maxillary sinusitis (CMS) based on CT image data to improve the accuracy of image d...

A comprehensive approach for osteoporosis detection through chest CT analysis and bone turnover markers: harnessing radiomics and deep learning techniques.

Frontiers in endocrinology
PURPOSE: The main objective of this study is to assess the possibility of using radiomics, deep learning, and transfer learning methods for the analysis of chest CT scans. An additional aim is to combine these techniques with bone turnover markers to...

ChronoMID-Cross-modal neural networks for 3-D temporal medical imaging data.

PloS one
ChronoMID-neural networks for temporally-varying, hence Chrono, Medical Imaging Data-makes the novel application of cross-modal convolutional neural networks (X-CNNs) to the medical domain. In this paper, we present multiple approaches for incorporat...

Translation of morphological and functional musculoskeletal imaging.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
In an effort to develop quantitative biomarkers for degenerative joint disease and fill the void that exists for diagnosing, monitoring, and assessing the extent of whole joint degeneration, the past decade has been marked by a greatly increased role...

Using deep-learning based segmentation to enable spatial evaluation of knee osteoarthritis (SEKO) in rodent models.

Osteoarthritis and cartilage
OBJECTIVE: In preclinical models of osteoarthritis (OA), histology is commonly used to evaluate joint remodeling. The current study introduces a deep learning driven histological analysis pipeline for the spatial evaluation of knee osteoarthritis (SE...

Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

PeerJ
BACKGROUND: Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal children, as assessed by the triglyceride-glucose (TyG) index, remains underexplored. Bone turnover mar...

Machine learning model for osteoporosis diagnosis based on bone turnover markers.

Health informatics journal
To assess the diagnostic utility of bone turnover markers (BTMs) and demographic variables for identifying individuals with osteoporosis. A cross-sectional study involving 280 participants was conducted. Serum BTM values were obtained from 88 patient...

Relation of Age, Sex and Bone Mineral Density to Serum 25-Hydroxyvitamin D Levels in Chinese Women and Men.

Orthopaedic surgery
OBJECTIVE: To investigate the relation of circulating 25-hydroxyvitamin D (25[OH]D) levels to age, sex, and bone mineral density (BMD) in adults living in Guangzhou Province.