Detection and segmentation of pathological structures by the extended graph-shifts algorithm

Jason J. Corso, Alan Yuille, Nancy L. Sicotte, Arthur Toga

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

26 Scopus citations

Abstract

We propose an extended graph-shifts algorithm for image segmentation and labeling. This algorithm performs energy minimization by manipulating a dynamic hierarchical representation of the image. It consists of a set of moves occurring at different levels of the hierarchy where the types of move, and the level of the hierarchy, are chosen automatically so as to maximally decrease the energy. Extended graph-shifts can be applied to a broad range of problems in medical imaging. In this paper, we apply extended graph-shifts to the detection of pathological brain structures: (i) segmentation of brain tumors, and (ii) detection of multiple sclerosis lesions. The energy terms in these tasks are learned from training data by statistical learning algorithms. We demonstrate accurate results, precision and recall in the order of 93%, and also show that the algorithm is computationally efficient, segmenting a full 3D volume in about one minute.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings
Pages985-993
Number of pages9
EditionPART 1
DOIs
StatePublished - 2007
Event10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007 - Brisbane, Australia
Duration: 29 Oct 20072 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4791 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007
Country/TerritoryAustralia
CityBrisbane
Period29/10/072/11/07

Fingerprint

Dive into the research topics of 'Detection and segmentation of pathological structures by the extended graph-shifts algorithm'. Together they form a unique fingerprint.

Cite this