LEPROSY DETECTION USING IMAGE PROCESSING AND DEEP LEARNING

Leprosy, generally called as Hansen's ailment, is an enervating and ceaseless bacterial malady. As indicated by World Health Organization's report, there were 189,000 uninterrupted occurrences of Leprosy in 2012 with 230,000 new conclusions. Though it is reparable at later stages, an early conclusion expects nerve deliberation and the inadequacies it causes. The makers thusly put forward a Convolutional Neural Network based building for Leprosy damage affirmation. To set up the framework, researchers and scientist use DermnetNz datasets close by web scratched pictures to finish a best accuracy of 91.6% on a dataset split into 60% of get ready pictures, 20% of pictures are used for cross endorsement and 20% for testing of the results.

[1]  Tanvir Parhar,et al.  Leprosy lesion recognition using convolutional neural networks , 2016, 2016 International Conference on Machine Learning and Cybernetics (ICMLC).

[2]  G. Schaefer,et al.  Overlay of thermal and visual medical images using skin detection and image registration , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.