Improved artificial intelligence discrimination of minor histological populations by supplementing with color-adjusted images.

ABSTRACT: Despite the dedicated research of artificial intelligence (AI) for pathological images, the construction of AI applicable to histopathological tissue subtypes, is limited by insufficient dataset collection owing to disease infrequency. Here, we present a solution involving the addition of supplemental tissue array (TA) images that are adjusted to the tonality of the main data using a cycle-consistent generative adversarial network (CycleGAN) to the training data for rare tissue types. F1 scores of rare tissue types that constitute < 1.2% of the training data were significantly increased by improving recall values after adding color-adjusted TA images constituting < 0.65% of total training patches. The detector also enabled the equivalent discrimination of clinical images from two distinct

SUBMITTER: Hatta S 

PROVIDER: S-EPMC10625567 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature