An Adaptive Linearized Method for Localizing Video Endoscopic Capsule Using Weighted Centroid Algorithm

Video Capsule Endoscope (VCE) sends images of abnormalities in the gastrointestinal (GI) tract. While the physicians receive these images, they have little idea of their exact location which is needed for proper treatment. The proposed localization system consists of a 3D antenna array (with 8 receiver sensors) and one transmitter embedded inside the electronic capsule. We propose an adaptive linearized method of localization using Weighted Centroid Localization (WCL) where the position is calculated by averaging the weighted sum of the reference positions. In our proposed system, first we identify the path loss attenuation exponents using linear least square regression of the collected data (RSSI versus distance). Then the path loss model is linearized to minimize the path loss deviation which is mainly caused due to the nonhomogeneous environment of radio propagation. Then the instantaneous path loss (PL) measured by the sensors is attenuated to the above linearized model and considered as the weight of the sensors to find the location of the capsule using WCL. Finally a calibration process is applied using linear least square regression. To assess the performance, we model the path loss and implement the algorithm in Matlab for 2,530 possible positions with a resolution of 1 mm. The results show that the algorithm achieves high localization accuracy compared with other related methods when simulated using a 3D small intestine model

Enabling technologies for MRI guided interventional procedures

This dissertation addresses topics related to developing interventional assistant devices for Magnetic Resonance Imaging (MRI). MRI can provide high-quality 3D visualization of target anatomy and surrounding tissue, but the benefits can not be readily harnessed for interventional procedures due to difficulties associated with the use of high-field (1.5T or greater) MRI. Discussed are potential solutions to the inability to use conventional mecha- tronics and the confined physical space in the scanner bore. This work describes the development of two apparently dissimilar systems that repre- sent different approaches to the same surgical problem - coupling information and action to perform percutaneous (through the skin) needle placement with MR imaging. The first system addressed takes MR images and projects them along with a surgical plan directly on the interventional site, thus providing in-situ imaging. With anatomical images and a corresponding plan visible in the appropriate pose, the clinician can use this information to perform the surgical action. My primary research effort has focused on a robotic assistant system that overcomes the difficulties inherent to MR-guided procedures, and promises safe and reliable intra-prostatic needle placement inside closed high-field MRI scanners. The robot is a servo pneumatically operated automatic needle guide, and effectively guides needles under real- time MR imaging. This thesis describes development of the robotic system including requirements, workspace analysis, mechanism design and optimization, and evaluation of MR compatibility. Further, a generally applicable MR-compatible robot controller is de- veloped, the pneumatic control system is implemented and evaluated, and the system is deployed in pre-clinical trials. The dissertation concludes with future work and lessons learned from this endeavor

EUROSENSORS XVII : book of abstracts

Fundação Calouste Gulbenkien (FCG).Fundação para a Ciência e a Tecnologia (FCT)