Improved Watershed Algorithm for CT Liver Segmentation Using Intraclass Variance Minimization-Reference-Cited by-同舟云学术

Improved Watershed Algorithm for CT Liver Segmentation Using Intraclass Variance Minimization

Published:2017 Issue: Volume: Page:164-176
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Mohamed Alaa Salah El-Din^ORCID,Salem Mohammed A.-M.^ORCID,Hegazy Doaa^ORCID,Shedeed Howida A.^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-67642-5_14

Reference16 articles.

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3. Mohamed, A.S.E.D., Salem, M.A.M., Hegazy, D., Shedeed, H.A.: Probablistic-based framework for medical CT images segmentation. In: 2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS), pp. 149–155. IEEE, Cairo (2015)

4. Lawankar, M., Sangewar, S., Gugulothu, S.: Segmentation of liver using marker watershed transform algorithm for CT scan images. In: 2016 International Conference on Communication and Signal Processing (ICCSP), pp. 0553–0556. IEEE, Melmaruvathur (2016)

5. Benson, C.C., Deepa, V., Lajish, V.L., Rajamani, K.: Brain tumor segmentation from MR brain images using improved fuzzy c-means clustering and watershed algorithm. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 187–192. IEEE, Jaipur (2016)

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