PET/CT图像分割及其发展现状
Research on PET/CT Image Segmentation and Its Development
查看参考文献56篇
文摘
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随着精准医疗技术的快速进步,PET/CT图像中病灶区域分割已在医疗计划制定中显现出重要作用.PET/CT将PET(功能代谢显像)和CT(解剖结构显像)两种先进的影像技术有机地结合在一起,是影像诊断学的一个重要进展.结合当前分割方法,本文详细介绍了PET/CT成像原理以及PET/CT图像的特点,对分割方法进行分类,深入分析各种方法的现状及其在肿瘤学中的应用.最后,进一步阐述了PET/CT图像分割技术的核心问题和发展趋势. |
其他语种文摘
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With the rapid progress of precision medical technology,the segmentation of lesion regions in PET/CT images has played an important role in the development of medical plans.PET/CT combines two advanced imaging technologies organically:PET (functional metabolic imaging) and CT (anatomical structure imaging),which is an important progress in image diagnostics.Combined with the segmentation methods,this paper describes the characteristics of PET/CT images,the analysis of the current methods and the clinical application.Finally,the paper elaborates the development trend of PET/CT image segmentation technology. |
来源
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电子学报
,2018,46(10):2504-2510 【核心库】
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DOI
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10.3969/j.issn.0372-2112.2018.10.026
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关键词
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精准医疗
;
PET/CT图像
;
分割方法
;
临床应用
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地址
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1.
辽宁师范大学计算机与信息技术学院, 辽宁, 大连, 116029
2.
大连理工大学电子信息与电气工程学部, 辽宁, 大连, 116023
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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0372-2112 |
学科
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自动化技术、计算机技术 |
基金
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中国博士后科学基金
;
国家自然科学基金
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文献收藏号
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CSCD:6364793
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参考文献 共
56
共3页
|
1.
National Research Council (US) Committee on a framework for developing a new tax.
Toward precision medicine:building a knowledge network for biomedical research and a new taxonomy of disease,2011
|
CSCD被引
5
次
|
|
|
|
2.
Dhara A K. Computer-aided detection and analysis of pulmonary nodule from CT images:a survey.
IETE Technical Review,2012,29(4):265-275
|
CSCD被引
3
次
|
|
|
|
3.
Ballangan C. Automated delineation of lung tumors in PET images based on monotonicity and a tumor-customized criterion.
IEEE Transactions on Information Technology in Biomedicine,2011,15(5):691-702
|
CSCD被引
1
次
|
|
|
|
4.
Fried D. MO-DE-207B-10:Impact of morphologic characteristics on radiomics features from contast-enhanced CT for primary lung tumors.
Medical Physics,2016,43(6):3706-3706
|
CSCD被引
1
次
|
|
|
|
5.
Daouk J. Effect of tomographic operator inaccuracies and respiratory motion on PET/CT lung nodule images smearing.
Nuclear Medicine Communications,2017,38(2):178-184
|
CSCD被引
1
次
|
|
|
|
6.
Nermina B. Advantages of combined PET-CT in mediastinal staging in patients with non-small cell lung carcinoma.
Acta Informatica Medica,2016,24(2):99-102
|
CSCD被引
2
次
|
|
|
|
7.
Zheng X. A hybrid clustering method for ROI delineation in small animal dynamic PET images:application to the automatic estimation of FDG input functions.
IEEE Engineering in Medicine & Biology Society,2011,15(2):195-205
|
CSCD被引
1
次
|
|
|
|
8.
Zsoter N. PET-CT based automated lung nodule detection.
IEEE Annual International Conference on Engineering in Medicine and Biology Society,2012:4974-4977
|
CSCD被引
1
次
|
|
|
|
9.
Mharib A M. Survey on liver CT image segmentation methods.
Artificial Intelligence Review,2012,37(2):83-95
|
CSCD被引
8
次
|
|
|
|
10.
Sharifi M. Optimized production,quality control,biological evaluation and PET/CT imaging of 68Ga-PSMA-617 in breast adenocarcinoma model.
Radio Chimica Acta,2017,105(5):399-407
|
CSCD被引
1
次
|
|
|
|
11.
Karki K. TU-H-CAMPUS-JeP2-02:Interobserver variability of CT,PET-CT and MRI based primary tumor delineation for lung cancer.
Medical Physics,2016,43(6):3782-3782
|
CSCD被引
1
次
|
|
|
|
12.
Hines J P. Positive and negative predictive value of PET-CT in skull base lesions:case series and systematic literature review.
J Neurol Surg Rep,2016,77(1):39-45
|
CSCD被引
1
次
|
|
|
|
13.
Biehl K J. 18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer:is a single standardized uptake value threshold approach appropriate?.
Journal of Nuclear Medicine,2006,47(11):1808-1812
|
CSCD被引
20
次
|
|
|
|
14.
Belhassen S. A novel fuzzy C-means algorithm for unsupervised heterogeneous tumor quantification in PET.
Medical Physics,2010,37(3):1309-1324
|
CSCD被引
1
次
|
|
|
|
15.
Mu W. A segmentation algorithm for quantitative analysis of heterogeneous tumors of the cervix with 18F-FDG PET/CT.
IEEE Transactions on Biomedical Engineering,2015,62(10):2465-2479
|
CSCD被引
2
次
|
|
|
|
16.
Xu Z. Fuzzy connectedness image co-segmentation for hybrid PET/MRI and PET/CT scans.
Computational Methods for Molecular Imaging,2015:15-24
|
CSCD被引
1
次
|
|
|
|
17.
Han D. Globally optimal tumor segmentation in PET-CT images:a graph-based co-segmentation method.
Information Processing in Medical Imaging,2011:245-256
|
CSCD被引
1
次
|
|
|
|
18.
Guo Y. Automatic lung tumor segmentation on PET/CT images using fuzzy markov random field model.
Computational and Mathematical Methods in Medicine,2014,1:171-188
|
CSCD被引
1
次
|
|
|
|
19.
Hussein S. Automatic segmentation and quantification of white and brown adipose tissues from PET/CT scans.
IEEE Transactions on Medical Imaging,2017,36(3):734-744
|
CSCD被引
2
次
|
|
|
|
20.
Wanet M. Gradient-based delineation of the primary GTV on FDG-PET in non-small cell lung cancer:a comparison with threshold-based approaches,CT and surgical specimens.
Journal of the European Society for Therapeutic Radiology & Oncology,2011,98(1):117-125
|
CSCD被引
4
次
|
|
|
|
|