• M.Karpakam
• Dr.P.Sumitra

The thyroid and cancer detection are diagnosis to Classification techniques play a vital as well as major role in analyzing suitability of diseases and providing the existing system and proposed system compare to analysis to graph. Thyroid with cancer also been detected worldwide and thus become a serious endocrine health problem and an issue of concern. Respected fresh thyroid with cancer tissues were imaged using Computerized Tomography (CT). In CT images, background and noise estimation as well as elimination were applied. Thyroid and cancer images were automatically segmented and modified histograms a calculated. Afterwards, features based on these histograms a calculated and it is proposed that these features can be used to discriminate malignant and benign thyroids with cancer. Moreover, as an indirect finding of histograms, it is concluded that thyroidal with cancer volume can be a useful criterion in determination of malignancy. The proposed work is efficient to algorithm using of CNN.

Thyroid and Cancer Disease, Support Vector Machine, Decision Tree, Naïve Bayes.CNN Algorithm, Classification.

"Thyroid and cancer Nodule Classification Based on Characteristic of Margin using Geometric and Statistical Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.671-677, June 2019, Available :http://www.jetir.org/papers/JETIR1907I84.pdf

"Thyroid and cancer Nodule Classification Based on Characteristic of Margin using Geometric and Statistical Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp671-677, June 2019, Available at : http://www.jetir.org/papers/JETIR1907I84.pdf