Screening of Sickle Cells Using Intelligent Microscope

Sickle cell disease (SCD) poses a foremost global health challenge, especially in developing countries where misdiagnosis is common. Timely diagnosis and treatment are crucial in preventing its high mortality rates. To enhance diagnosis, we've created an automated SCD screening system utilizing deep learning. Our method involves two networks that enhance low-resolution microscope images and accurately identify sickle cells. In blind tests, we achieved an impressive accuracy of 96.7%. This costeffective, precise microscope stands as a valuable tool for identifying SCD and addressing blood disorders in resource-constrained areas.