Detail publikace

Content-aware low-rank plus sparse model for perfusion MRI reconstruction

Originální název

Content-aware low-rank plus sparse model for perfusion MRI reconstruction

Anglický název

Content-aware low-rank plus sparse model for perfusion MRI reconstruction

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

BibTex


@misc{BUT128072,
  author="Marie {Mangová} and Pavel {Rajmic}",
  title="Content-aware low-rank plus sparse model for perfusion MRI reconstruction",
  annote="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.",
  chapter="128072",
  howpublished="online",
  year="2016",
  month="june",
  pages="1--1",
  type="presentation"
}