Call For Paper Volume:4 Issue:10 Oct'2017 |

Computer aided classification of Bascal cell carcinoma using adaptive Neuro-fuzzy Inference System

Publication Date : 30/08/2014



Author(s) :

Rajvi Parikh.


Volume/Issue :
Volume 1
,
Issue 2
(08 - 2014)



Abstract :

For skin lesion detection pathologists examine biopsies to make diagnostic assessment largely based on cell anatomy and tissue distribution. However in many instances it is subjective and often leads to considerable variability. Whereas computer diagnostic tools enable objective judgments by making use of quantitative measures. Paper presents a diagnosis system based on an adaptive Neuro-fuzzy inference system for effective classification of Bascal cell carcinoma images from the given set of all types of skin lesions. System divide in three parts. Image Processing, Feature Extraction, and classification. First part deals with the noise reduction and artifacts removing from the set of images. Second part deals with extracting variety of features of Bascal Cell Carcinoma using the Greedy feature flip algorithm (G-flip), and classification method using ANFIS algorithm and finally Part three deals with the results that is classification of BCC images from the variety of pre-cancerous stage images that is Actinic Keratosis and also other images called psoriasis which looks as cancer images at a first look . The results confirmed that the proposed ANFIS model has potential in classifying the skin cancer diagnosis.


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Computer aided classification of Bascal cell carcinoma using adaptive Neuro-fuzzy Inference System

December 2, 2014