Dr. Bappaditya Mandal recent publication to IET Computer Vision

This is in collaboration between Keele University, UK and Indian Institute of Technology, Bhubaneshwar, India, on detection of melanomas skin cancers using computer vision and deep learning methodologies.

Short synopsis: Of all the skin cancer that is prevalent, melanoma has the highest mortality rates. Melanoma becomes life threatening when it penetrates deep into the dermis layer unless detected at an early stage, it becomes fatal since it has a tendency to migrate to other parts of our body. Fig. 1 shows a few examples of dermoscopy skin images. This paper presents an automated non-invasive methodology to assist the clinicians and dermatologists for detection of melanoma. In this work, a deep convolutional neural network based regularized discriminant learning framework that extracts low dimensional discriminative features for melanoma detection is proposed. Experimental results on ISBI 2016, MED-NODE, PH2 and the recent ISBI 2017 databases show the efficacy of our proposed approach as compared to other state-of-the-art methodologies.

Details in the Keele repository: http://eprints.keele.ac.uk/5121/


Athena Swan