ISSN (Online) : 2456 - 0774

Email :

ISSN (Online) 2456 - 0774



Abstract:-Now a day’s Medical pictures are too fuzzy for lots discrete boundaries. Thisthesis describes a fuzzy rule primarily based seed factor optimizationtechnique in Fuzzy C-Means clustering approach with a utility in segmentationmanner. The maximum important facts about the idea helps to increase thecluster and capable of identify the target seed point smoothly for thedetection of renal calculi regularly referred to as a kidney stones. Thistechnique makes the entire concept a modern one wherein Kidney is a sourceorgan for urology disorder which may be included by means of green kidney stonedetection method in CT pictures. Proposed method of clustering reduces therange of iterations for elaborating the area of interest in allowed pictures.This approach gifted to present a more correct answer for CT pix and it enhancesthe image retrieval in comparison to classical clustering tactics. Theexperimental outcomes justify the effectiveness of proposed approach vialowering the computational time without effecting the segmentation quality inan best possible way.

Full Text PDF


Submit paper at

Paper Submission Open For June 2023
UGC indexed in (Old UGC) 2017
Last date for paper submission 30th June, 2023
Deadline Submit Paper any time
Publication of Paper Within 01-02 Days after completing all the formalities
Paper Submission Open For Publication /online Conference 
Publication Fees  
Free for PR Students