OsteoNet—A Framework for Identifying Osteoporosis in Bone Radiograph Images Using Attention-Based VGG Network
Diagnosing osteoporosis from X-ray images poses a significant challenge due to the visual similarities between images from healthy subjects and patients. In this paper, we present a novel method for detecting osteoporosis. Our approach utilizes local phase quantization (LPQ) to identify fine texture...
Saved in:
Main Authors: | Abdul Wahab Muzaffar, Farhan Riaz, Muhammad Tahir |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10872902/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Analysis of the Rate and Reasons for Rejected Radiographs in Emergency and Non-Emergency Radiology Departments in Yasuj, Iran
by: Seyyed Amir Moradian, et al.
Published: (2025-01-01) -
Prevent Osteoporosis: Catch the Silent Thief
by: Linda B. Bobroff
Published: (2017-05-01) -
Radiographic localization of supernumerary teeth: a narrative review
by: Sreekanth Kumar Mallineni, et al.
Published: (2025-02-01) -
THE EFFECTIVENESS OF ZINC AND RISEDRONATE ON BONE TURNOVER IN RAT MODEL OF OSTEOPOROSIS ASSESSED WITH THE EXPRESSION OF β-CROSSLAPS
by: Adam Fajar, et al.
Published: (2019-12-01) -
Jingui Shenqi Wan alleviates bone loss induced by primary osteoporosis by inhibiting osteoblast pyroptosis
by: Yuwangxuan Qian, et al.
Published: (2025-02-01)