Development of a system for the automatic recognition and classification of normal and abnormal cells in human blood samples

Automation of medical diagnosis/detection process is very important in terms of enhancing diagnostic accuracy, increasing throughput, reducing cost, and training new staff. Our current goal is to go from the proof of concept stage (automatic recognition and classification of human blood images) to a complete working optimized prototype and to start testing it in an actual clinical lab environment with help from CLS. The prototype design will take into account user friendliness, high throughput, robustness, integration with existing lab work flow and reasonable cost. Our goal is to decrease the processing time to 0.1 seconds through code optimizations and parallel programming and also increase the accuracy to be better than 95% which is the acceptable range in comparison with manual processing. Smartlabs aims to start a line of products based on this development

Faculty Supervisor:

Dr. Behrouz Far

Student:

Tamer Mohamed

Partner:

Smart Labs Ltd.

Discipline:

Engineering - computer / electrical

Sector:

Medical devices

University:

University of Calgary