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Found 5 papers, 0 papers with code
MAMOC: MRI Motion Correction via Masked Autoencoding
The presence of motion artifacts in magnetic resonance imaging (MRI) scans poses a significant challenge, where even minor patient movements can lead to artifacts that may compromise the scan's utility.
Privacy Protection in MRI Scans Using 3D Masked Autoencoders
Data anonymization and de-identification is concerned with ensuring the privacy and confidentiality of individuals' personal information.
Wide Range MRI Artifact Removal with Transformers
Our method is realized through the design of a novel volumetric transformer-based neural network that generalizes a \emph{window-centered} approach popularized by the Swin transformer.
Conditional De-Identification of 3D Magnetic Resonance Images
Solutions have been developed to de-identify diagnostic scans by obfuscating or removing parts of the face.
Adversarial Privacy Preservation in MRI Scans of the Brain
De-identification of magnetic resonance imagery (MRI) is intrinsically difficult since, even with all metadata removed, a person's face can easily be rendered and matched against a database.
