  Wireless Capsule Endoscopy (WCE) is a relatively new technology to record the
entire GI trace, in vivo. The large amounts of frames captured during an
examination cause difficulties for physicians to review all these frames. The
need for reducing the reviewing time using some intelligent methods has been a
challenge. Polyps are considered as growing tissues on the surface of
intestinal tract not inside of an organ. Most polyps are not cancerous, but if
one becomes larger than a centimeter, it can turn into cancer by great chance.
The WCE frames provide the early stage possibility for detection of polyps.
Here, the application of simple linear iterative clustering (SLIC) superpixel
for segmentation of polyps in WCE frames is evaluated. Different SLIC
superpixel numbers are examined to find the highest sensitivity for detection
of polyps. The SLIC superpixel segmentation is promising to improve the results
of previous studies. Finally, the superpixels were classified using a support
vector machine (SVM) by extracting some texture and color features. The
classification results showed a sensitivity of 91%.
