Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images. (arXiv:2202.12267v2 [eess.IV] UPDATED)

In the application of deep learning on optical coherence tomography (OCT)
data, it is common to train classification networks using 2D images originating
from volumetric data. Given the micrometer resolution of OCT systems,
consecutive images are often very similar in both visible structures and noise.
Thus, an inappropriate data split can result in overlap between the training
and testing sets, with a large portion of the literature overlooking this
aspect. In this study, the effect of improper dataset splitting on …

accuracy arxiv classification data data leakage deep learning images inflation test