The aim of this project is to use the camera and processing power of modern day cell phones to develop an intuitive and user-friendly application for the detection and concentration estimation of various bio-markers in blood sample images. It is later planned to be used as a screening test for cancer. The application will allow the user to take images of the blood samples in a set format. The image will then be segmented to detect the regions of interest. After noise removal, the intensity of each individual blob will be calculated. A linear curve will be fit through the intensity and known concentration data and the concentrations of the unknown samples will be estimated from the standard curve which will quantify the various molecules present in the sample. The aim of the project this year was to develop the iOS version of ConcAnalyzer which was developed for Android last year.
This project is a continuation of last year's work which can be found in this repository. Before implementing last year's algorithm in iOS, it was changed in some respects to get better accuracy and results from all the 3 channels of the input image. This changed algorithm was first added to the Android version of the application and then the iOS version was developed. A list of commits can be found below.
The algorithm used for detection of regions of interest is same as last year which can be found here (Points 1-9). Only the algorithm for concentration estimation has been changed which is explained below.
I'm indebted to Dr. Tomas Helikar for giving me the opportunity of working on this amazing project. I would also like to thank Daniel Cohen Gindi & Philipp Jahoda, whose library, Charts, has been used in this project. It has been released under Apache License 2.0.
Also, Thank you, Google. 😀