2019
DOI: 10.48550/arxiv.1907.02431
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From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI

Roman Beliy,
Guy Gaziv,
Assaf Hoogi
et al.

Abstract: Reconstructing observed images from fMRI brain recordings is challenging. Unfortunately, acquiring sufficient "labeled" pairs of {Image, fMRI} (i.e., images with their corresponding fMRI responses) to span the huge space of natural images is prohibitive for many reasons. We present a novel approach which, in addition to the scarce labeled data (training pairs), allows to train fMRI-to-image reconstruction networks also on "unlabeled" data (i.e., images without fMRI recording, and fMRI recording without images)… Show more

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