Electrical Engineering and Systems Science > Image and Video Processing
arXiv:2310.04871 (eess)
[Submitted on 7 Oct 2023]
Title:Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging
View a PDF of the paper titled Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging, by Ke Xiao and 4 other authors
View PDFAbstract:Mitral regurgitation (MR) is a heart valve disease with potentially fatal consequences that can only be forestalled through timely diagnosis and treatment. Traditional diagnosis methods are expensive, labor-intensive and require clinical expertise, posing a barrier to screening for MR. To overcome this impediment, we propose a new semi-supervised model for MR classification called CUSSP. CUSSP operates on cardiac imaging slices of the 4-chamber view of the heart. It uses standard computer vision techniques and contrastive models to learn from large amounts of unlabeled data, in conjunction with specialized classifiers to establish the first ever automated MR classification system. Evaluated on a test set of 179 labeled -- 154 non-MR and 25 MR -- sequences, CUSSP attains an F1 score of 0.69 and a ROC-AUC score of 0.88, setting the first benchmark result for this new task.
| Comments: | 12 pages including references and the appendix. 9 Figures, 2 tables. Accepted at MICCAI (Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging) 2023, Link to Springer atthis https URL |
| Subjects: | Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG) |
| ACM classes: | I.4.0; I.2.10 |
| Cite as: | arXiv:2310.04871 [eess.IV] |
| (orarXiv:2310.04871v1 [eess.IV] for this version) | |
| https://doi.org/10.48550/arXiv.2310.04871 arXiv-issued DOI via DataCite | |
| Journal reference: | In: Medical Image Computing and Computer Assisted Intervention - MICCAI 2023. pp. 236-246 (2023) |
| Related DOI: | https://doi.org/10.1007/978-3-031-43990-2_23 DOI(s) linking to related resources |
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View a PDF of the paper titled Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging, by Ke Xiao and 4 other authors
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