Detection and density estimation of goblet cells in confocal endoscopy for the evaluation of celiac disease.

Celiac Disease (CD) is an immune-mediated enteropathy, diagnosed in the clinical practice by intestinal biopsy and the concomitant presence of a positive celiac serology. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to potentially perform in vivo virtual histology of small-bowel mucosa. In particular, it allows the qualitative evaluation of mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a semi-automatic computer-based method for the detection of goblet cells from confocal endoscopy images, whose density changes in case of pathological tissue. After a manual selection of a suitable region of interest, the candidate columnar and goblet cells' centers are first detected and the cellular architecture is estimated from their position using a Voronoi diagram. The region within each Voronoi cell is then analyzed and classified as goblet cell or other. The results suggest that our method is able to detect and label goblet cells immersed in a columnar epithelium in a fast, reliable and automatic way. Accepting 0.44 false positives per image, we obtain a sensitivity value of 90.3%. Furthermore, estimated and real goblet cell densities are comparable (error: 9.7 ± 16.9%, correlation: 87.2%, R(2) = 76%).