ImUnity: A generalizable VAE-GAN solution for multicenter MR image harmonization
| العنوان: | ImUnity: A generalizable VAE-GAN solution for multicenter MR image harmonization |
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| المؤلفون: | Stenzel Cackowski, Emmanuel L. Barbier, Michel Dojat, Thomas Christen |
| المصدر: | Medical Image Analysis. 88:102799 |
| بيانات النشر: | Elsevier BV, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | FOS: Computer and information sciences, Computer Science - Machine Learning, Radiological and Ultrasound Technology, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Computer Vision and Pattern Recognition, Health Informatics, Radiology, Nuclear Medicine and imaging, Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing, Computer Graphics and Computer-Aided Design, Machine Learning (cs.LG) |
| الوصف: | ImUnity is an original deep-learning model designed for efficient and flexible MR image harmonization. A VAE-GAN network, coupled with a confusion module and an optional biological preservation module, uses multiple 2D-slices taken from different anatomical locations in each subject of the training database, as well as image contrast transformations for its self-supervised training. It eventually generates 'corrected' MR images that can be used for various multi-center population studies. Using 3 open source databases (ABIDE, OASIS and SRPBS), which contain MR images from multiple acquisition scanner types or vendors and a large range of subjects ages, we show that ImUnity: (1) outperforms state-of-the-art methods in terms of quality of images generated using traveling subjects; (2) removes sites or scanner biases while improving patients classification; (3) harmonizes data coming from new sites or scanners without the need for an additional fine-tuning and (4) allows the selection of multiple MR reconstructed images according to the desired applications. Tested here on T1-weighted images, ImUnity could be used to harmonize other types of medical images. 15 pages, 7 Figures |
| تدمد: | 1361-8415 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e24715f86d3b02da7a103d72f689e365 https://doi.org/10.1016/j.media.2023.102799 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....e24715f86d3b02da7a103d72f689e365 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 13618415 |
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