Handling Missing MRI Data in Brain Tumors Classification Tasks: Usage of Synthetic Images vs. Duplicate Images and Empty Images
Yael H. Moshe MS 1,2, Yuval Buchsweiler BS 1,3, Mina Teicher PhD 2,4, Moran Artzi PhD 1,5,6
Sagol Brain Institute, Tel Aviv Sourasky Medical Center
2 Department of Mathematics Bar Ilan University Ramat Gan Israel
3 The Iby and Aladar Fleischman Faculty of Engineering Tel Aviv University Tel Aviv Israel
4 Gonda Brain Research Center Bar‐Ilan University Ramat Gan Israel
5 Faculty of Medicine Tel Aviv University Tel Aviv Israel
6 Sagol School of Neuroscience Tel Aviv University Tel Aviv Israel
Background Deep‐learning is widely used for lesion classification. However, in the clinic patient data often has missing images.
Purpose To evaluate the use of generated, duplicate and empty(black) images for replacing missing MRI data in AI brain tumor classification tasks.
Study Type Retrospective.
Population 224 patients (local‐dataset; low‐grade‐glioma (LGG) = 37, high‐grade‐glioma...
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