ItemArticle

Novel Approach for Osteoporosis Classification Using X-ray Images

Title
Novel Approach for Osteoporosis Classification Using X-ray Images
Creator
Dodamani, Pooja Shivanand; Palanisamy, Kanmani; Danti, Ajit
Description
This research delves into the technical advancements of image segmentation and classification models, specifically the refined Pix2Pix and Vision Transformer (ViT) architectures, for the crucial task of osteoporosis detection using X-ray images. The improved Pix2Pix model demonstrates noteworthy strides in image segmentation, achieving a specificity of 97.24% and excelling in the reduction of false positives. Simultaneously, the modified ViT models, especially the MViT-B/16 variant, exhibit superior accuracy at 96.01% in classifying osteoporosis cases, showcasing their proficiency in identifying critical medical conditions. These models are poised to revolutionize osteoporosis diagnosis, providing clinicians with accurate tools for early detection and intervention. The synergies between the Pix2Pix and ViT models open avenues for nuanced approaches in automated diagnostic systems, with the potential to significantly improve clinical results and contribute to the broader landscape of medical image analysis. As osteoporosis remains a prevalent and often undiagnosed condition, the technical insights from this study hold substantial importance in advancing the field, emphasizing the critical role of accurate diagnostic tools in improving patient care and health outcomes. 2025 Oriental Scientific Publishing Company. All rights reserved.
Source
Biomedical and Pharmacology Journal;Volume;18;pp.203-216
Date
01-01-2025
Publisher
Oriental Scientific Publishing Company
Subject
BMD; Osteoporosis; Pix2Pix Segmentation; ViT Classification; X-ray Images
Coverage
Dodamani P.S., Computer Science and Engineering, Christ University, Bangalore, India; Palanisamy K., Christ University, Computer Science and Engineering, CSE, Bangalore, India; Danti A., Computer Science and Engineering, Christ University, Bangalore, India
Rights
All Open Access; Gold Open Access
Relation
ISSN: 9746242;
Format
online
Language
English
Type
Article

Citation

Dodamani, Pooja Shivanand; Palanisamy, Kanmani; Danti, Ajit, “Novel Approach for Osteoporosis Classification Using X-ray Images,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/23219.

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