1. Blood Cell Recognizer & Counter Group 13

2. Group Members Praboda Gabadage (030297) Oshani Seneviratne (030355) Omega Silva (030368) Vidakna Soyza (030372)

3. Project Supervisor Dr. Chatura De Silva Senior Lecturer Department of Computer Science and Engineering

4. Introduction Analysis of human blood is very important in diagnosing diseases Blood cell recognition and counting play a crucial role Examples Dengue Malaria Anemia Bacterial deceases

5. Background In Sri Lanka, Blood counting and recognition is done manually Government hospitals provide the facility for free of charge But not enough to meet the demand In case of a pandemic outbreak…????

6. Available Solutions Blood cell counting machines Use laser beams to count. Blood cell counting Software Solutions Uses Image processing technologies All the solutions are very expensive The government cannot afford such solutions

7. Our Solution To develop a software based solution that would do the following Accept the digital image of the blood cells with a higher magnification Recognize different types of blood cells (e.g. Platelets) Count those blood cells separately Provides standard blood count report A stand alone application + web service

8. Advantages Efficiency through automation Cost effective Eliminate human errors Easy to manipulate and robust Remote access

9. Possible Extensions Recognizing other biological cells E.g. Cancer cells Provide medical diagnosis with percentage of accuracy

10. Q & A

11. Thank You!