Multi-atlas based segmentation editing with interaction-guided constraints

Sang Hyun Park, Yaozong Gao, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


We propose a novel multi-atlas based segmentation method to address the editing scenario, when given an incomplete segmentation along with a set of training label images. Unlike previous multi-atlas based methods, which depend solely on appearance features, we incorporate interaction-guided constraints to find appropriate training labels and derive their voting weights. Specifically, we divide user interactions, provided on erroneous parts, into multiple local interaction combinations, and then locally search for the training label patches well-matched with each interaction combination and also the previous segmentation. Then, we estimate the new segmentation through the label fusion of selected label patches that have their weights defined with respect to their respective distances to the interactions. Since the label patches are found to be from different combinations in our method, various shape changes can be considered even with limited training labels and few user interactions. Since our method does not need image information or expensive learning steps, it can be conveniently used for most editing problems. To demonstrate the positive performance, we apply our method to editing the segmentation of three challenging data sets: prostate CT, brainstem CT, and hippocampus MR. The results show that our method outperforms the existing editing methods in all three data sets.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings
EditorsAlejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783319245737
Publication statusPublished - 2015
Externally publishedYes
Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: 2015 Oct 52015 Oct 9

Publication series

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


Other18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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