Mapping multi-modal routine imaging data to a single reference via multiple templates

Johannes Hofmanninger, Bjoern Menze, Marc André Weber, Georg Langs

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Population level analysis of medical imaging data relies on finding spatial correspondence across individuals as a basis for local comparison of visual characteristics. Here, we describe and evaluate a framework to normalize routine images covering different parts of the human body, in different modalities to a common reference space. The framework performs two basic steps towards normalization: (1) The identification of the location and coverage of the human body by an image and (2) a non-linear mapping to the common reference space. Based on these mappings, either coordinates, or label-masks can be transferred across a population of images. We evaluate the framework on a set of routine CT and MR scans exhibiting large variability on location and coverage. A set of manually annotated landmarks is used to assess the accuracy and stability of the approach. We report distinct improvement in stability and registration accuracy compared to a classical single-atlas approach.

Original languageEnglish
Title of host publicationDeep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - 3rd International Workshop, DLMIA 2017 and 7th International Workshop, ML-CDS 2017 Held in Conjunction with MICCAI 2017, Proceedings
EditorsTal Arbel, M. Jorge Cardoso
PublisherSpringer Verlag
Pages341-348
Number of pages8
ISBN (Print)9783319675572
DOIs
StatePublished - 2017
Event3rd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 and 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 14 Sep 201714 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10553 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 and 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period14/09/1714/09/17

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