Fuzzy Clustering Technique for Segmentation on Skin Cancer Dermoscopic Images-Reference-Cited by-同舟云学术

Fuzzy Clustering Technique for Segmentation on Skin Cancer Dermoscopic Images

Published:2022 Issue: Volume: Page:81-89
ISSN:1434-9922
Container-title:Fuzzy Mathematical Analysis and Advances in Computational Mathematics
language:
Short-container-title:

Author:

Kavitha M.,Senthil Arumugam A.,Hong Tzung-Pei

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-0471-4_6

Reference21 articles.

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2. Meskini, E.M.S., Helfroush, K.K., Sepaskhah, M.: A new algorithm for skin lesion border detection in dermoscopy images. J. Biomed. Phys. Eng. 8, 117–126 (2018)

3. Kavitha, M., Senthil Arumugam, A., Saravana Kumar, V.: Enhanced clustering technique for segmentation on dermoscopic images. In: IEEE—4th International Conference on Intelligent Computing and Control Systems (ICICCS 2020), Madurai, TN, May, pp. 956–961 (2020). https://doi.org/10.1109/ICICCS48265.2020.9121102

4. Schaefer, G., Rajab, M.I., Emre Celebi, M., Iyatomi, H.: Colour and contrast enhancement for improved skin lesion segmentation. Comput. Med. Imaging Gr. 35(2), 99–104 (2011). https://doi.org/10.1016/j.compmedimag.2010.08.004

5. Barata, C., Celebi, M.E., Marques, J.S.: A survey of feature extraction in dermoscopy image analysis of skin cancer. IEEE J. Biomed. Health Inform. 23(3), 1096–1109 (2019). https://doi.org/10.1109/JBHI.2018.2845939

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