11 datasets found

The Hyper-Kvasir dataset contains 10,662 images labeled with anatomical landmarks as well as pathological and normal findings.

Highly imbalanced datasets are ubiquitous in medical image classification problems. In such problems, it is often the case that rare classes associated to less prevalent...

Brain tumor MRI dataset used for classification of brain tumors into Meningioma, Glioma, and Pituitary tumor

A dataset of retinal images for diabetic retinopathy grading.

A dataset of X-rays for tuberculosis control.

A dataset of posterior-anterior X-rays for tuberculosis control.

A dataset of chest X-ray images of children with pneumonia.

The dataset used in the paper for zero-shot medical image classification, pneumonia, tuberculosis, retinopathy, and brain tumor.

The dataset used in the paper is Fed-ISIC2019, which is a medical image classification dataset. It contains 23,247 samples across eight melanoma classes.

Breast cancer image classification method based on deep transfer learning

The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used a dataset for medical image classification, specifically for diabetic...