Examination of the whole gastrointestinal tract represents a challenge for endoscopists due to its length and inaccessibility using natural orifices. Moreover, radiologic techniques are relatively insensitive for diminutive, flat, infiltrative, or inflammatory lesions of the small bowel. Since 1994, video capsules (VCEs) have been developed to allow direct examination of this inaccessible part of the gastrointestinal tract and to help doctors to find the cause of symptoms such as stomach pain, disease of Crohn, diarrhoea, weight loss, rectal bleeding, and anaemia. The Pillcam© video capsule designed by Given Imaging Company is the most popular of them. This autonomous embedded system allows acquiring about fifty thousand images of gastrointestinal tract during more than twelve hours of an analysis. However, acquired images are of low resolution and imaging conditions could be very poor as the movements and the speed of the VCE as illumination are not entirely controlled all along the transit of the capsule through the whole gastrointestinal tract. As a consequence segmentation of VCE images is a real challenging problem: first of all specialists need a flexible segmentation tool that makes delineations of very different structures (polyps, metastasis... to name a few) possible and second, the proposed method should be efficient even in difficult imaging conditions. In this article, an adapted segmentation method based on statistical active contours for VCE segmentation is proposed and tested on various types of gastrointestinal structures.