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Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques
Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades. MRI is free of...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699322/ https://www.ncbi.nlm.nih.gov/pubmed/31467888 http://dx.doi.org/10.1155/2019/3843295 |
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author | Chan, Si-Wa Chang, Yung-Chieh Huang, Po-Wen Ouyang, Yen-Chieh Chang, Yu-Tzu Chang, Ruey-Feng Chai, Jyh-Wen Chen, Clayton Chi-Chang Chen, Hsian-Min Chang, Chein-I. Lin, Chin-Yao |
author_facet | Chan, Si-Wa Chang, Yung-Chieh Huang, Po-Wen Ouyang, Yen-Chieh Chang, Yu-Tzu Chang, Ruey-Feng Chai, Jyh-Wen Chen, Clayton Chi-Chang Chen, Hsian-Min Chang, Chein-I. Lin, Chin-Yao |
author_sort | Chan, Si-Wa |
collection | PubMed |
description | Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades. MRI is free of the problems related to radiation exposure and provides excellent image resolution and contrast. However, a disadvantage is the injection of contrast agent, which is toxic for some patients (such as patients with chronic renal disease or pregnant and lactating women). Recent findings of gadolinium deposits in the brain are also a concern. To address these issues, this paper develops an intravoxel incoherent motion- (IVIM-) MRI-based histogram analysis approach, which takes advantage of several hyperspectral techniques, such as the band expansion process (BEP), to expand a multispectral image to hyperspectral images and create an automatic target generation process (ATGP). After automatically finding suspected targets, further detection was attained by using kernel constrained energy minimization (KCEM). A decision tree and histogram analysis were applied to classify breast tissue via quantitative analysis for detected lesions, which were used to distinguish between three categories of breast tissue: malignant tumors (i.e., central and peripheral zone), cysts, and normal breast tissues. The experimental results demonstrated that the proposed IVIM-MRI-based histogram analysis approach can effectively differentiate between these three breast tissue types. |
format | Online Article Text |
id | pubmed-6699322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-66993222019-08-29 Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques Chan, Si-Wa Chang, Yung-Chieh Huang, Po-Wen Ouyang, Yen-Chieh Chang, Yu-Tzu Chang, Ruey-Feng Chai, Jyh-Wen Chen, Clayton Chi-Chang Chen, Hsian-Min Chang, Chein-I. Lin, Chin-Yao Biomed Res Int Research Article Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades. MRI is free of the problems related to radiation exposure and provides excellent image resolution and contrast. However, a disadvantage is the injection of contrast agent, which is toxic for some patients (such as patients with chronic renal disease or pregnant and lactating women). Recent findings of gadolinium deposits in the brain are also a concern. To address these issues, this paper develops an intravoxel incoherent motion- (IVIM-) MRI-based histogram analysis approach, which takes advantage of several hyperspectral techniques, such as the band expansion process (BEP), to expand a multispectral image to hyperspectral images and create an automatic target generation process (ATGP). After automatically finding suspected targets, further detection was attained by using kernel constrained energy minimization (KCEM). A decision tree and histogram analysis were applied to classify breast tissue via quantitative analysis for detected lesions, which were used to distinguish between three categories of breast tissue: malignant tumors (i.e., central and peripheral zone), cysts, and normal breast tissues. The experimental results demonstrated that the proposed IVIM-MRI-based histogram analysis approach can effectively differentiate between these three breast tissue types. Hindawi 2019-07-28 /pmc/articles/PMC6699322/ /pubmed/31467888 http://dx.doi.org/10.1155/2019/3843295 Text en Copyright © 2019 Si-Wa Chan et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chan, Si-Wa Chang, Yung-Chieh Huang, Po-Wen Ouyang, Yen-Chieh Chang, Yu-Tzu Chang, Ruey-Feng Chai, Jyh-Wen Chen, Clayton Chi-Chang Chen, Hsian-Min Chang, Chein-I. Lin, Chin-Yao Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques |
title | Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques |
title_full | Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques |
title_fullStr | Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques |
title_full_unstemmed | Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques |
title_short | Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques |
title_sort | breast tumor detection and classification using intravoxel incoherent motion hyperspectral imaging techniques |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699322/ https://www.ncbi.nlm.nih.gov/pubmed/31467888 http://dx.doi.org/10.1155/2019/3843295 |
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