3D alpha matting based co-segmentation of tumors on PET-CT images

Zisha Zhong, Yusung Kim, John Buatti, Xiaodong Wu

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

13 Scopus citations

Abstract

Positron emission tomography – computed tomography (PET-CT) has been widely used in modern cancer imaging. Accurate tumor delineation from PET and CT plays an important role in radiation therapy. The PET-CT co-segmentation technique, which makes use of advantages of both modalities, has achieved impressive performance for tumor delineation. In this work, we propose a novel 3D image matting based semi-automated co-segmentation method for tumor delineation on dual PET-CT scans. The “matte” values generated by 3D image matting are employed to compute the region costs for the graph based co-segmentation. Compared to previous PET-CT co-segmentation methods, our method is completely data-driven in the design of cost functions, thus using much less hyper-parameters in our segmentation model. Comparative experiments on 54 PET-CT scans of lung cancer patients demonstrated the effectiveness of our method.

Original languageEnglish (US)
Title of host publicationMolecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment - 5th International Workshop, CMMI 2017 2nd International Workshop, RAMBO 2017 and 1st International Workshop, SWITCH 2017 Held in Conjunction with MICCAI 2017, Proceedings
EditorsM. Jorge Cardoso, Tal Arbel
PublisherSpringer Verlag
Pages31-42
Number of pages12
ISBN (Print)9783319675633
DOIs
StatePublished - 2017
Externally publishedYes
Event5th International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, 2nd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 and 1st International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: Sep 14 2017Sep 14 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10555 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, 2nd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 and 1st International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period9/14/179/14/17

Keywords

  • Co-segmentation
  • Image matting
  • Image segmentation
  • Interactive segmentation
  • Lung tumor segmentation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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