IEICE TRANSACTIONS on Information
An Interleaved Otsu Segmentation for MR Images with Intensity Inhomogeneity
Summary :
The MR image segmentation is always a challenging problem because of the intensity inhomogeneity. Many existing methods don't reach their expected segmentations; besides their implementations are usually complicated. Therefore, we originally interleave the extended Otsu segmentation with bias field estimation in an energy minimization. Via our proposed method, the optimal segmentation and bias field estimation are achieved simultaneously throughout the reciprocal iteration. The results of our method not only satisfy the required classification via its applications in the synthetic and the real images, but also demonstrate that our method is superior to the baseline methods in accordance with the performance analysis of JS metrics.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.11 pp.2974-2978
- Publication Date
- 2014/11/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDL8042
- Type of Manuscript
- LETTER
- Category
- Biological Engineering
Authors
Haoqi XIONG
University of Electronic Science and Technology of China
Jingjing GAO
University of Electronic Science and Technology of China
Chongjin ZHU
University of Electronic Science and Technology of China
Yanling LI
Chongqing University
Shu ZHANG
University of Electronic Science and Technology of China
Mei XIE
University of Electronic Science and Technology of China
Keyword
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Haoqi XIONG, Jingjing GAO, Chongjin ZHU, Yanling LI, Shu ZHANG, Mei XIE, "An Interleaved Otsu Segmentation for MR Images with Intensity Inhomogeneity" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 11, pp. 2974-2978, November 2014, doi: 10.1587/transinf.2014EDL8042.
Abstract: The MR image segmentation is always a challenging problem because of the intensity inhomogeneity. Many existing methods don't reach their expected segmentations; besides their implementations are usually complicated. Therefore, we originally interleave the extended Otsu segmentation with bias field estimation in an energy minimization. Via our proposed method, the optimal segmentation and bias field estimation are achieved simultaneously throughout the reciprocal iteration. The results of our method not only satisfy the required classification via its applications in the synthetic and the real images, but also demonstrate that our method is superior to the baseline methods in accordance with the performance analysis of JS metrics.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDL8042/_p
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@ARTICLE{e97-d_11_2974,
author={Haoqi XIONG, Jingjing GAO, Chongjin ZHU, Yanling LI, Shu ZHANG, Mei XIE, },
journal={IEICE TRANSACTIONS on Information},
title={An Interleaved Otsu Segmentation for MR Images with Intensity Inhomogeneity},
year={2014},
volume={E97-D},
number={11},
pages={2974-2978},
abstract={The MR image segmentation is always a challenging problem because of the intensity inhomogeneity. Many existing methods don't reach their expected segmentations; besides their implementations are usually complicated. Therefore, we originally interleave the extended Otsu segmentation with bias field estimation in an energy minimization. Via our proposed method, the optimal segmentation and bias field estimation are achieved simultaneously throughout the reciprocal iteration. The results of our method not only satisfy the required classification via its applications in the synthetic and the real images, but also demonstrate that our method is superior to the baseline methods in accordance with the performance analysis of JS metrics.},
keywords={},
doi={10.1587/transinf.2014EDL8042},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - An Interleaved Otsu Segmentation for MR Images with Intensity Inhomogeneity
T2 - IEICE TRANSACTIONS on Information
SP - 2974
EP - 2978
AU - Haoqi XIONG
AU - Jingjing GAO
AU - Chongjin ZHU
AU - Yanling LI
AU - Shu ZHANG
AU - Mei XIE
PY - 2014
DO - 10.1587/transinf.2014EDL8042
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2014
AB - The MR image segmentation is always a challenging problem because of the intensity inhomogeneity. Many existing methods don't reach their expected segmentations; besides their implementations are usually complicated. Therefore, we originally interleave the extended Otsu segmentation with bias field estimation in an energy minimization. Via our proposed method, the optimal segmentation and bias field estimation are achieved simultaneously throughout the reciprocal iteration. The results of our method not only satisfy the required classification via its applications in the synthetic and the real images, but also demonstrate that our method is superior to the baseline methods in accordance with the performance analysis of JS metrics.
ER -
English
