The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018

12 Aug 2019Nicholas HellerJack RickmanChristopher WeightNikolaos Papanikolopoulos

Widely-used public benchmarks are of huge importance to computer vision and machine learning research, especially with the computational resources required to reproduce state of the art results quickly becoming untenable. In medical image computing, the wide variety of image modalities and problem formulations yields a huge task-space for benchmarks to cover, and thus the widespread adoption of standard benchmarks has been slow, and barriers to releasing medical data exacerbate this issue... (read more)

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