@article{(Open Science Index):https://publications.waset.org/pdf/10004525,
	  title     = {Medical Image Edge Detection Based on  Neuro-Fuzzy Approach },
	  author    = {J. Mehena and  M. C. Adhikary},
	  country	= {},
	  institution	= {},
	  abstract     = {Edge detection is one of the most important tasks in image processing. Medical image edge detection plays an important role in segmentation and object recognition of the human organs. It refers to the process of identifying and locating sharp discontinuities in medical images. In this paper, a neuro-fuzzy based approach is introduced to detect the edges for noisy medical images. This approach uses desired number of neuro-fuzzy subdetectors with a postprocessor for detecting the edges of medical images. The internal parameters of the approach are optimized by training pattern using artificial images. The performance of the approach is evaluated on different medical images and compared with popular edge detection algorithm. From the experimental results, it is clear that this approach has better performance than those of other competing edge detection algorithms for noisy medical images.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {10},
	  number    = {1},
	  year      = {2016},
	  pages     = {229 - 232},
	  ee        = {https://publications.waset.org/pdf/10004525},
	  url   	= {https://publications.waset.org/vol/109},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 109, 2016},
	}