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DAŇKOVÁ, M. RAJMIC, P.
Original Title
Content-aware low-rank plus sparse model for perfusion MRI reconstruction
Type
presentation
Language
English
Original Abstract
Perfusion magnetic resonance imaging is a promising diagnostic method in medicine. In order to perform perfusion analysis, leading to e.g. revealing a tumor, one starts with acquiring the anatomical image before injecting the contrast agent. Based on the inferred spatial distribution of organs, we develop a natural, content-aware, way of extension of the low-rank plus sparse model for reconstruction of undersampled perfusion MRI data.
Keywords
MRI, compressed sensing, perfusion, L+S model
Authors
DAŇKOVÁ, M.; RAJMIC, P.
Released
6. 6. 2016
Location
Strobl, Rakousko
Pages from
1
Pages to
Pages count
BibTex
@misc{BUT128072, author="Marie {Mangová} and Pavel {Rajmic}", title="Content-aware low-rank plus sparse model for perfusion MRI reconstruction", year="2016", pages="1--1", address="Strobl, Rakousko", note="presentation" }