Conference proceeding
3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images
Molecular imaging, reconstruction and analysis of moving body organs, and stroke imaging and treatment : Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Vol.10555, pp.31-42
09/2017
DOI: 10.1007/978-3-319-67564-0_4
PMCID: PMC6886662
PMID: 31799515
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.
Details
- Title: Subtitle
- 3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images
- Creators
- Zisha Zhong - University of IowaYusung Kim - University of IowaJohn Buatti - University of IowaXiaodong Wu - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Molecular imaging, reconstruction and analysis of moving body organs, and stroke imaging and treatment : Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Vol.10555, pp.31-42
- DOI
- 10.1007/978-3-319-67564-0_4
- PMID
- 31799515
- PMCID
- PMC6886662
- eISBN
- 9783319675640; 3319675648
- ISSN
- 0302-9743
- eISSN
- 1611-3349
- Language
- English
- Date published
- 09/2017
- Academic Unit
- Electrical and Computer Engineering; Radiation Oncology; The Iowa Institute for Biomedical Imaging; Neurosurgery; Otolaryngology
- Record Identifier
- 9984197289302771
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