Biomedical and Health Sciences

Access the dataset for images of typical diabetic retinopathy lesions and also normal retinal structures annotated at a pixel level, focused on an Indian population. This dataset provides information on the disease severity of diabetic retinopathy, and diabetic macular edema for each image.

The published sEMG database was captured by the Intelligent System and Biomedical Robotics Group at University of Portsmouth, leaded by Prof. Honghai Liu.

Six subjects were volunteered for data capturing, and the sEMG data were captured in ten separate days. We manually separated the whole database into two parts: training dataset (the first 7 days) and testing dataset(the last 3 days). For each subject, two folders exist, one for training and the other for test. 

TB (Tuberculosis) is a contagious disease which is caused by a bacterium named Mycobacterium Tuberculosis. Screening is done to confirm the presence of TB using different screening techniques available i.e. Chest X-ray, Microscopy, Gene Xpert and Culture etc. Medical image processing is a rapidly growing field of image processing that is used to automate different medical procedures. In this research we have designed two automated systems for the screening of TB patients. A sample of 50 images for microscopy slides and chest X-ray radiographs were taken.

This cell images dataset is collected using an ultrafast imaging system known as asymmetric-detection time-stretch optical microscopy (ATOM)  for training and evaluation. This novel imaging approach can achieve label-free and high-contrast flow imaging with good cellular resolution images at a very high speed. Each acquired image belongs to one of the four classes: THP1, MCF7, MB231 and PBMC.