Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The automation system in the medical image processing become a high impact for the real world applications. In that, most of the disease are can be identified by the basic instrument with medical assist such as normal camera, smartphones etc. that are externally exposed in the human body. Related to that, the melanoma skin cancer can predict with the images based on the color of the ROI and the texture of it. In this paper, the texture based melanoma image prediction techniques was discussed with the pattern classification methods. In this, the texture pattern of the image was extracted by the Octo-Directional image pattern method. Thus it focused on the different projection angle of the image mask to find the difference in neighboring pixels. This will estimate the depth of the image compare to traditional image pattern methods. The results were tested and compared with the other state-of-art methods that justifies the performance of the Octo-directionality prediction model.
"A Comparative Analysis on Texture Pattern Feature Extraction Methods in Melanoma Prediction", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.2180 - 2190, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206329.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator