Automated hip dysplasia detection using novel FlexiLBPHOG model with ultrasound images
Article
Article Title | Automated hip dysplasia detection using novel FlexiLBPHOG model with |
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ERA Journal ID | 211692 |
Article Category | Article |
Authors | Key, Sefa, Kurum, Huseyin, Esmez, Omer, Hafeez-Baig, Abdul, Hajiyeva, Rena, Dogan, Sengul and Tuncer, Turker |
Journal Title | Ain Shams Engineering Journal |
Journal Citation | 16 (1) |
Article Number | 103235 |
Number of Pages | 12 |
Year | 2025 |
Publisher | Ain Shams University |
Elsevier | |
Place of Publication | Egypt |
ISSN | 2090-4479 |
2090-4495 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.asej.2024.103235 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S2090447924006166 |
Abstract | This study focuses on automatically detecting developmental hip dysplasia (DHD) using a novel feature engineering model, FlexiLBPHOG, inspired by the FlexiViT model. The model utilizes five patch types for feature extraction with local binary pattern (LBP) and histogram of oriented gradients (HOG) techniques. During feature extraction, five feature vectors are generated. In the next stage, three feature selection methods—Neighborhood Component Analysis (NCA), Chi-square (Chi2), and ReliefF (RF)—are used to select the top 500 features. Classification is performed using support vector machine (SVM) and k-nearest neighbors (kNN), resulting in 30 outcomes. Information fusion through iterative majority voting (IMV) and a greedy algorithm yields 58 outcomes, from which the best is selected. The FlexiLBPHOG model achieved a classification accuracy of 94.38% in detecting DHD in ultrasound images from a private dataset. The study confirms the effectiveness of the proposed model in image classification by integrating shallow image descriptors. |
Keywords | Development hip dysplasia detection; FlexiLBPHOG; Multiple feature selection; Information fusion; Ultrasound |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 420302. Digital health |
Byline Affiliations | Firat University, Turkey |
Elazig Fethi Sekin City Hospital, Turkey | |
School of Business | |
Western Caspian University, Azerbaijan |
https://research.usq.edu.au/item/zqx91/automated-hip-dysplasia-detection-using-novel-flexilbphog-model-with-ultrasound-images
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Automated hip dysplasia detection using novel FlexiLBPHOG model with ultrasound images.pdf | ||
License: CC BY-NC-ND 4.0 | ||
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