IntelliCardiac: An Intelligent Platform for Cardiac Image Segmentation and Classification
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866913826038874112 |
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| author | Tsai, Ting Yu Yu, An Maadugundu, Meghana Spurthi Mohima, Ishrat Jahan Barsha, Umme Habiba Chen, Mei-Hwa F. Prabhakaran, Balakrishnan Chang, Ming-Ching |
| author_facet | Tsai, Ting Yu Yu, An Maadugundu, Meghana Spurthi Mohima, Ishrat Jahan Barsha, Umme Habiba Chen, Mei-Hwa F. Prabhakaran, Balakrishnan Chang, Ming-Ching |
| contents | Precise and effective processing of cardiac imaging data is critical for the identification and management of the cardiovascular diseases. We introduce IntelliCardiac, a comprehensive, web-based medical image processing platform for the automatic segmentation of 4D cardiac images and disease classification, utilizing an AI model trained on the publicly accessible ACDC dataset. The system, intended for patients, cardiologists, and healthcare professionals, offers an intuitive interface and uses deep learning models to identify essential heart structures and categorize cardiac diseases. The system supports analysis of both the right and left ventricles as well as myocardium, and then classifies patient's cardiac images into five diagnostic categories: dilated cardiomyopathy, myocardial infarction, hypertrophic cardiomyopathy, right ventricular abnormality, and no disease. IntelliCardiac combines a deep learning-based segmentation model with a two-step classification pipeline. The segmentation module gains an overall accuracy of 92.6%. The classification module, trained on characteristics taken from segmented heart structures, achieves 98% accuracy in five categories. These results exceed the performance of the existing state-of-the-art methods that integrate both segmentation and classification models. IntelliCardiac, which supports real-time visualization, workflow integration, and AI-assisted diagnostics, has great potential as a scalable, accurate tool for clinical decision assistance in cardiac imaging and diagnosis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_03838 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | IntelliCardiac: An Intelligent Platform for Cardiac Image Segmentation and Classification Tsai, Ting Yu Yu, An Maadugundu, Meghana Spurthi Mohima, Ishrat Jahan Barsha, Umme Habiba Chen, Mei-Hwa F. Prabhakaran, Balakrishnan Chang, Ming-Ching Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Precise and effective processing of cardiac imaging data is critical for the identification and management of the cardiovascular diseases. We introduce IntelliCardiac, a comprehensive, web-based medical image processing platform for the automatic segmentation of 4D cardiac images and disease classification, utilizing an AI model trained on the publicly accessible ACDC dataset. The system, intended for patients, cardiologists, and healthcare professionals, offers an intuitive interface and uses deep learning models to identify essential heart structures and categorize cardiac diseases. The system supports analysis of both the right and left ventricles as well as myocardium, and then classifies patient's cardiac images into five diagnostic categories: dilated cardiomyopathy, myocardial infarction, hypertrophic cardiomyopathy, right ventricular abnormality, and no disease. IntelliCardiac combines a deep learning-based segmentation model with a two-step classification pipeline. The segmentation module gains an overall accuracy of 92.6%. The classification module, trained on characteristics taken from segmented heart structures, achieves 98% accuracy in five categories. These results exceed the performance of the existing state-of-the-art methods that integrate both segmentation and classification models. IntelliCardiac, which supports real-time visualization, workflow integration, and AI-assisted diagnostics, has great potential as a scalable, accurate tool for clinical decision assistance in cardiac imaging and diagnosis. |
| title | IntelliCardiac: An Intelligent Platform for Cardiac Image Segmentation and Classification |
| topic | Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2505.03838 |