In this work, bioengineering methods that can be used to quantitatively analyze videocapsule endoscopy images that have been acquired from celiac patients versus controls are described. For videocapsule endoscopic analysis, each patient swallows a capsule which contains an imaging device and light source. In celiac and control patients, images are acquired and analyzed at the level of the small intestine. The data used for videocapsule analysis consisted of high resolution images of dimension 576 × 576 pixels, acquired twice per second. The goal of the quantitative analysis is to detect abnormality in celiac patient images as compared with controls. Several types of abnormality can exist at the level of the small intestine in celiac patients. In untreated patients, and often even after treatment with a gluten-free diet, there can be villous atrophy, as well as presence of fissures and a mottled appearance. To detect and discern these abnormalities, several methods of statistical and structural feature extraction and selection are described. It was found that there is a significantly greater variation in image texture and average brightness level in celiac patients as compared with controls (p < 0.05). Celiac patients have a longer dominant period as compared with controls, averaging 6.4 ± 2.6 seconds versus 4.7 ± 1.6 seconds in controls (p = 0.001). This suggests that overall motility is slower in the celiac patients. Furthermore, the mean number of villous protrusions per image was found to be 402.2±15.0 in celiac patients versus 420.8±24.0 in control patients (p < 0.001). The average protrusion width was 14.66±1.04 pixels in celiacs versus 13.91±1.47 pixels in controls (p = 0.01). The mean protrusion height was 3.10±0.26 grayscale levels for celiacs versus 2.70±0.43 grayscale levels for controls (p < 0.001). Thus celiac patients tended to have fewer protrusions, and these were more varied in shape, tending to be blunted, as compared with controls, which more often had fine, uniform protrusions. A variety of computerized methods are now available to quantitate videocapsule images for comparison of celiac versus control patients. Since these methods are based on computer algorithms, they can be automated and there is no variation in the results due to observer bias. These methods readily lend themselves to automation, so that it may be possible to map the entire small intestine for presence of abnormality in real-time. It is also possible to develop an automated, quantitative clinical score which can be displayed with real-time update during the procedure. This would be useful to determine progress in celiac patients on a gluten-free diet, and to better understand the properties of the healing process in these patients.