Capsule endoscope localization based on visual features

Computational analysis of wireless capsule endoscopy (WCE) videos has already proved its potentials in the discovery or characterization of lesions and in the reduction of the time required by the endoscopists to perform the examination. An open problem that has only partially been addressed is the localization of the capsule endoscope in the gastrointestinal (GI) tract. Previous works have been based mainly on external, wearable, sensors. In this paper we propose a novel approach based solely on visual information extracted from WCE videos. This approach is based on a feature tracking method for visual odometry, which enables the estimation of both the rotation and the displacement of a capsule endoscope from reference anatomical landmarks. Its implementation is based on a novel, open access Java Video Analysis (JVA) framework, which enables quick and standardized development of intelligent video analysis applications. The experimental evaluation presented in this paper, indicates the feasibility of the proposed methodological approach and the efficiency of its implementation.