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Self-Supervised Transformers for fMRI representation. (arXiv:2112.05761v2 [eess.IV] UPDATED)
Aug. 16, 2022, 1:13 a.m. | Itzik Malkiel, Gony Rosenman, Lior Wolf, Talma Hendler
cs.CV updates on arXiv.org arxiv.org
We present TFF, which is a Transformer framework for the analysis of
functional Magnetic Resonance Imaging (fMRI) data. TFF employs a two-phase
training approach. First, self-supervised training is applied to a collection
of fMRI scans, where the model is trained to reconstruct 3D volume data.
Second, the pre-trained model is fine-tuned on specific tasks, utilizing ground
truth labels. Our results show state-of-the-art performance on a variety of
fMRI tasks, including age and gender prediction, as well as schizophrenia
recognition. Our …
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