Structure specific atlas generation and its application to pancreas segmentation from contrasted abdominal CT volumes

Ken’Ichi Karasawa, Takayuki Kitasaka, Masahiro Oda, Yukitaka Nimura, Yuichiro Hayashi, Michitaka Fujiwara, Kazunari Misawa, Daniel Rueckert, Kensaku Mori

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

8 Zitate (Scopus)

Abstract

Patient-specific atlas is a key technology for the recognition of the human anatomy from 3D medical images. Automated recognition of the pancreas is one main issue for computer-assisted diagnosis and therapy systems in the abdomen because many diseases of the pancreas are not accompanied by noticeable symptoms. In patient-specific atlas generation, hierarchical and mosaicing methods have been proposed to cope with individual differences in the position, orientation, and shape of the pancreas. Even though segmentation accuracy was improved by these methods, it remains lower than for other abdominal organs, such as the liver and the kidneys. The location of the pancreas strongly correlates with the location of vasculature systems, especially the splenic vein. In this paper, we propose a new structure specific atlas generation method that considers the structural information in atlas generation. As for the structural information, we enhance the vasculature using a vesselness filter. Similar volumes in a training dataset with respect to the vasculature structure are selected and used for atlas generation. Using 150 cases of contrast-enhanced 3D abdominal CT volumes, our experiment improved the mis-segmentation of the surrounding organs or such soft tissues as the duodenum.

OriginalspracheEnglisch
TitelMedical Computer Vision
UntertitelAlgorithms for Big Data - International Workshop, MCV 2015 and Held in Conjunction with MICCAI 2015, Revised Selected Papers
Redakteure/-innenMichael Kelm, Henning Müller, Bjoern Menze, Shaoting Zhang, Dimitris Metaxas, Georg Langs, Albert Montillo, Weidong Cai
Herausgeber (Verlag)Springer Verlag
Seiten47-56
Seitenumfang10
ISBN (Print)9783319420158
DOIs
PublikationsstatusVeröffentlicht - 2016
Extern publiziertJa
VeranstaltungInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI - Germany, Deutschland
Dauer: 9 Okt. 20159 Okt. 2015

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band9601 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

KonferenzInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI
Land/GebietDeutschland
OrtGermany
Zeitraum9/10/159/10/15

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