Exploring large scale public medical image datasets

Understand

Rationale and Objectives: Medical artificial intelligence systems are dependent on well characterised large scale datasets.

• Recently released public datasets have been of great interest to the field, but pose specific challenges due to the disconnect they cause between data generation and data usage, potentially limiting the utility of these datasets.
• Materials and Methods: We visually explore two large public datasets, to determine how accurate the provided labels are and whether other subtle problems exist.
• The ChestXray14 dataset contains 112,120 frontal chest films, and the MURA dataset contains 40,561 upper limb radiographs.