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  Published Paper Details:

  Paper Title

A SURVEY ON DIAGNOSIS OF SKIN CANCER BASED ON IMAGE PROCESSING USING MACHINE LEARNING

  Authors

  Snehal Vijay Kamble,  Dr. P.R. Gumble

  Keywords

Skin Cancer, Skin Lesion, Melanoma, Image Processing, Machine Learning

  Abstract


In a human body, skin is the core part, which helps to cover the muscles, bones what's more with the entire body. These days numerous people are suffering from skin cancer. Malignant melanoma is the deadliest form of skin cancer. The most serious type of cancer is Melanoma, which is the enormous type of skin malignant growth and the extent of these skin cancer is increasing day by day. Melanoma can be easily treatable if detected in early stages. Clinical as well as automated methods are being used for melanoma diagnosis. Image-based computer aided diagnosis systems have great potential for early malignant melanoma detection. Recognizing the type of skin cancer automatically from the images can assist in the quick diagnosis and enhanced accuracy saving valuable time. This paper presents review on automated diagnosis of skin cancer by analyzing image using Image Processing techniques with applying intelligence using Machine Learning. The purpose of this bibliographic review is to provide researchers opting to work in implementing machine learning learning for cancer diagnosis a knowledge from scratch of the state-of-the-art achievements.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2106191

  Paper ID - 208385

  Page Number(s) - b523-b528

  Pubished in - Volume 9 | Issue 6 | June 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Snehal Vijay Kamble,  Dr. P.R. Gumble,   "A SURVEY ON DIAGNOSIS OF SKIN CANCER BASED ON IMAGE PROCESSING USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 6, pp.b523-b528, June 2021, Available at :http://www.ijcrt.org/papers/IJCRT2106191.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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