Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method
Scoliosis is a disease caused by the spine curving. It is treatable but physiotherapists may do different measurements for curvature angles. That’s a problem affecting the treatment planning. This study aims to develop a Deep Learning-based decision support system, which diagnoses scolios...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9975279/ |
| _version_ | 1828116564652589056 |
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| author | Sena Goral Utku Kose |
| author_facet | Sena Goral Utku Kose |
| author_sort | Sena Goral |
| collection | DOAJ |
| description | Scoliosis is a disease caused by the spine curving. It is treatable but physiotherapists may do different measurements for curvature angles. That’s a problem affecting the treatment planning. This study aims to develop a Deep Learning-based decision support system, which diagnoses scoliosis and plans treatments via Schroth method. The system has an interpretable and explainable CapsNet model processing x-ray image to detect 68-point vertebrae and make Cobb angle measurements. By using angle values and patient parameters, treatment is planned through an automated Schroth definition and the Fuzzy Logic. In the evaluations, the CapsNet had dominating findings (some of them are MSE: 0.0038, PCC: 0.93, Accuracy: 0.98). The Fuzzy Logic model was accurate at exercise plans for past cases. Also, physiotherapists and patients had positive feedback for the system usage, trustworthiness, diagnosis, treatment planning and tracking. As a conclusion, the system ensures advancements for automated diagnosis and treatment of scoliosis. |
| first_indexed | 2024-04-11T12:58:50Z |
| format | Article |
| id | doaj.art-e32c0afdf66e4c4f83bb17c777b893ff |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T12:58:50Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e32c0afdf66e4c4f83bb17c777b893ff2022-12-22T04:23:00ZengIEEEIEEE Access2169-35362022-01-011012905512907810.1109/ACCESS.2022.32277639975279Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth MethodSena Goral0Utku Kose1https://orcid.org/0000-0002-9652-6415Information Systems Engineering, Mehmet Akif Ersoy University, Burdur, TurkeyComputer Engineering, Suleyman Demirel University, Isparta, TurkeyScoliosis is a disease caused by the spine curving. It is treatable but physiotherapists may do different measurements for curvature angles. That’s a problem affecting the treatment planning. This study aims to develop a Deep Learning-based decision support system, which diagnoses scoliosis and plans treatments via Schroth method. The system has an interpretable and explainable CapsNet model processing x-ray image to detect 68-point vertebrae and make Cobb angle measurements. By using angle values and patient parameters, treatment is planned through an automated Schroth definition and the Fuzzy Logic. In the evaluations, the CapsNet had dominating findings (some of them are MSE: 0.0038, PCC: 0.93, Accuracy: 0.98). The Fuzzy Logic model was accurate at exercise plans for past cases. Also, physiotherapists and patients had positive feedback for the system usage, trustworthiness, diagnosis, treatment planning and tracking. As a conclusion, the system ensures advancements for automated diagnosis and treatment of scoliosis.https://ieeexplore.ieee.org/document/9975279/ScoliosisCapsNetdeep learningfuzzy logicdecision support system |
| spellingShingle | Sena Goral Utku Kose Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method IEEE Access Scoliosis CapsNet deep learning fuzzy logic decision support system |
| title | Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method |
| title_full | Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method |
| title_fullStr | Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method |
| title_full_unstemmed | Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method |
| title_short | Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method |
| title_sort | development of a capsnet and fuzzy logic decision support system for diagnosing the scoliosis and planning treatments via schroth method |
| topic | Scoliosis CapsNet deep learning fuzzy logic decision support system |
| url | https://ieeexplore.ieee.org/document/9975279/ |
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