Reflekt

Project Description-Reflekt aims to use simple camera will take photos of a user’s body every day, and algorithms will cull and crop the photos to create a profile for each mole. “So for each mole, there will be a historical record that shows what it looks like, the estimated size changes over time, discolorations, changes at the edges. Reflect could provide the doctor with a kind of dashboard that displays significant changes. “It might say that out of 15 moles on patient A’s body, two of them look like they have higher than that patient’s average mole growth in the last six months. This would give doctors more information and context than they get now with only annual or biennial visits.This would be like detecting early stage skin cancer. With approximate 7% rise in skin cancer , this methodology would be a cost effective, time saving using a camera.

Methodology The setup would consists of a two-way mirror with a display monitor behind it, with the reflective ratio of the mirror allowing the user to see themselves as well as what’s on-screen behind the glass. The setup will also be equipped with a Raspberry Pi, a computer the size of a credit card on which pylon application will be built How to build pylon applications on Raspberry Pi

The idea is that Reflekt will take photos of a user’s body every day, and algorithms will cull and crop the photos to create a profile for each mole. “So for each mole, there will be a historical record that shows what it looks like, the estimated size changes over time, discolorations, changes at the edges Will have to simulate camera via machine learning to cover every fraction of human body via hands wide side ways and legs opened up to shoulder width pose.

With reference being screen behind mirror in which visible image (this will coincident with image formed by camera's on the screen)it would be accompanied by a green signal and buzzer(to acknowledge that successful image has been taken) for cameras to have every human body part (frontal , side , back)in focus.Once frontal part is fine , the sides and back will simply be turning around the same point.

Challenges- 1)For quick scan multiple cameras will be required and the data can be clubbed up for use. 2)Nude images need to be taken care off by coding protection. 3)Parts like inner thigh, arm pits imaging would be a challenge 4) 3D scan to detect moles frontal , side and back. One of the biggest challenges is to get enough of the right kind of data to train their models to identify moles accurately.