  Celiac Disease (CD) is a chronic autoimmune disease that affects the small
intestine in genetically predisposed children and adults. Gluten exposure
triggers an inflammatory cascade which leads to compromised intestinal barrier
function. If this enteropathy is unrecognized, this can lead to anemia,
decreased bone density, and, in longstanding cases, intestinal cancer. The
prevalence of the disorder is 1% in the United States. An intestinal (duodenal)
biopsy is considered the "gold standard" for diagnosis. The mild CD might go
unnoticed due to non-specific clinical symptoms or mild histologic features. In
our current work, we trained a model based on deep residual networks to
diagnose CD severity using a histological scoring system called the modified
Marsh score. The proposed model was evaluated using an independent set of 120
whole slide images from 15 CD patients and achieved an AUC greater than 0.96 in
all classes. These results demonstrate the diagnostic power of the proposed
model for CD severity classification using histological images.
