A Variational Method for Contructing Unbiased Atlas with Probabilistic Label Maps

Kanglin  Chen; Alexander Derksen

A Variational Method for Contructing Unbiased Atlas with Probabilistic Label Maps

Kanglin Chen^*, Alexander Derksen

^*Corresponding author for this work

Institute of Mathematics and Image Computing

Fraunhofer MEVIS

Abstract

We introduce a novel variational method based image registration and reconstruction to construct an average atlas with probabilistic label maps. The average atlas equipped with probabilistic label maps could be used to improve atlas based segmentation. In the experiment we validate the registration accuracy and the unbiasedness of atlas construction using clinical datasets.

Original language	English
Title of host publication	Informatik aktuell
Publisher	Springer International Publishing
Publication date	01.01.2015
Publication status	Published - 01.01.2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Cite this

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title = "A Variational Method for Contructing Unbiased Atlas with Probabilistic Label Maps",

abstract = "We introduce a novel variational method based image registration and reconstruction to construct an average atlas with probabilistic label maps. The average atlas equipped with probabilistic label maps could be used to improve atlas based segmentation. In the experiment we validate the registration accuracy and the unbiasedness of atlas construction using clinical datasets.",

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