Thin blood smear images of red blood cells with rouleaux formation morphology and normal morphology

This dataset contains images of thin blood smear with normal red blood cell morphology and rouleaux red blood cell morphology. Ethical approval with approval number: NHREC/17/03//2018 was obtained from Kano state ministry of health. Blood samples from 100 malaria infected patients were collected from Asiya Bayero pediatric hospital, kano state, Nigeria. Thick and thin blood smear slides were prepared using field stain. To ensure there was no bias in slide preparation, slides used for hospital diagnosis prepared under limited and constrained conditions were used as such types of slides represent the true reality of malaria diagnosis in less developed countries.Thin blood smear microscopy was performed by an expert microscopist and each slide was labeled according to the presence of Rouleaux formation or not among others. Out of 100 samples collected, 28 samples had rouleaux formation morphology.

A 12MP iPhone 10 camera was attached to a microscope’s eyepiece. Pictures of different field of views for each slide were captured using the iPhone’s camera. For each slide, a minimum of 10 different field of views were captured. 616 images were captured for slides with rouleaux formation. To create a balanced dataset an equal number, 616 images were also captured for slides with normal morphology. To increase the size and variation of the dataset. 312 Digital images of thin blood smear slides with Giemsa staining collected from Murtala Muhammad specialist hospital were added. out of the 312 images, 156 had rouleaux RBC morphology and 156 had normal RBC morphology. Image capture was conducted in the morning, afternoon and evening and in different rooms with different lighting conditions to introduce diverse levels of illumination in the images The captured images from both hospitals had a size of 4032x3024 pixels. The background of the images were cropped to give a size 2500x2500 which were then sliced to give a final size of 750x750 pixels. The final data set consists of 12,356 thin blood smear images with rouleaux formation morphology and 12,356 thin blood smear images with normal red blood cell morphology. Different CNN architectures were trained for the binary classification of the dataset.