NeuroDerm: Intelligent Skin Disorder Diagnosis Using ML

Skin conditions are the most common in health problems throughout the world. These illnesses have hidden risks that can be lead to physical discomfort and occasionally even depression. Skin cancer may even result from severe cases. One of this most of the challenging tasks in medical image processing is the diagnosis of skin disorders from clinical photographs. When completed by medical professionals by hand, it takes a lot of this time and is subjective. Thus, in way to expedite the process in developing the treatment plans for the patients and the dermatologists, an automatic method for predicting skin diseases is must required. In this our work, we suggest a method for digital hair removal that combines an inpainting algorithm with morphological filtering, such as Black-Hat transformation, and then uses Gaussian filtering to de-noise or de-blur the images. To separate the impacted lesions, we additionally employ the automated Grabcut segmentation method. In the way to identify patterns in the skin photos,