Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm
In this study, an effective means for detecting cancer region through different types of medical image segmentation are presented and explained. We proposed a new method for cancer segmentation on the basis of fuzzy entropy with a level set (FELs) thresholding. The proposed method was successfully u...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2018-09-01
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| Series: | Open Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/med-2018-0056 |
| _version_ | 1818720509195452416 |
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| author | Maolood Ismail Yaqub Al-Salhi Yahya Eneid Abdulridha Lu Songfeng |
| author_facet | Maolood Ismail Yaqub Al-Salhi Yahya Eneid Abdulridha Lu Songfeng |
| author_sort | Maolood Ismail Yaqub |
| collection | DOAJ |
| description | In this study, an effective means for detecting cancer region through different types of medical image segmentation are presented and explained. We proposed a new method for cancer segmentation on the basis of fuzzy entropy with a level set (FELs) thresholding. The proposed method was successfully utilized to segment cancer images and then efficiently performed the segmentation of test ultrasound image, brain MRI, and dermoscopy image compared with algorithms proposed in previous studies. Results showed an excellent performance of the proposed method in detecting cancer image segmentation in terms of accuracy, precision, specificity, and sensitivity measures. |
| first_indexed | 2024-12-17T20:23:58Z |
| format | Article |
| id | doaj.art-72ded0fa772f4707a952139a9b815f8e |
| institution | Directory Open Access Journal |
| issn | 2391-5463 |
| language | English |
| last_indexed | 2024-12-17T20:23:58Z |
| publishDate | 2018-09-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Medicine |
| spelling | doaj.art-72ded0fa772f4707a952139a9b815f8e2022-12-21T21:33:51ZengDe GruyterOpen Medicine2391-54632018-09-0113137438310.1515/med-2018-0056med-2018-0056Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithmMaolood Ismail Yaqub0Al-Salhi Yahya Eneid Abdulridha1Lu Songfeng2School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, ChinaSchool of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, ChinaSchool of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, ChinaIn this study, an effective means for detecting cancer region through different types of medical image segmentation are presented and explained. We proposed a new method for cancer segmentation on the basis of fuzzy entropy with a level set (FELs) thresholding. The proposed method was successfully utilized to segment cancer images and then efficiently performed the segmentation of test ultrasound image, brain MRI, and dermoscopy image compared with algorithms proposed in previous studies. Results showed an excellent performance of the proposed method in detecting cancer image segmentation in terms of accuracy, precision, specificity, and sensitivity measures.https://doi.org/10.1515/med-2018-0056image segmentationfuzzy entropylevel set algorithmthresholding cancer segmentation |
| spellingShingle | Maolood Ismail Yaqub Al-Salhi Yahya Eneid Abdulridha Lu Songfeng Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm Open Medicine image segmentation fuzzy entropy level set algorithm thresholding cancer segmentation |
| title | Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm |
| title_full | Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm |
| title_fullStr | Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm |
| title_full_unstemmed | Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm |
| title_short | Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm |
| title_sort | thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm |
| topic | image segmentation fuzzy entropy level set algorithm thresholding cancer segmentation |
| url | https://doi.org/10.1515/med-2018-0056 |
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