A non-rigid map fusion-based direct SLAM method for endoscopic capsule robots

Mehmet Turan,Helder Araujo,Metin Sitti,Yasin Almalioglu,Ender Konukoglu

doi:10.1007/s41315-017-0036-4

Abstract

Since the development of capsule endoscopy technology, medical device companies and research groups have made significant progress to turn passive capsule endoscopes into robotic active capsule endoscopes. However, the use of robotic capsules in endoscopy still has some challenges. One such challenge is the precise localization of the actively controlled robot in real-time. In this paper, we propose a non-rigid map fusion based direct simultaneous localization and mapping method for endoscopic capsule robots. The proposed method achieves high accuracy for extensive evaluations of pose estimation and map reconstruction performed on a non-rigid, realistic surgical EsophagoGastroDuodenoscopy Simulator and outperforms state-of-the art methods.

Highlights

In the past decade, advances in microsensors and microelectronics have enabled small, low cost devices in a variety of high impact applications
Many challenges posed by the GI tract and low quality cameras of the endoscopic capsule robots cause further difficulties in front of a vision-based localization and mapping methods (vSLAM) technique to be applied in a medical operation
We developed a direct medical vSLAM method which shows high accuracy in terms of map reconstruction and pose estimation inside GI tract

Summary

Introduction

Advances in microsensors and microelectronics have enabled small, low cost devices in a variety of high impact applications Following these advances, untethered pill-size, swallowable capsule endoscopes with an onboard camera and wireless image transmission device have been developed and used in hospitals for screening the gastrointestinal (GI) tract and diagnosing diseases such as the inflammatory bowel disease, the ulcerative colitis, and the. As a solution of these issues, vision-based localization and mapping methods (vSLAM) have attracted the attention for small-scale medical devices. With their low cost and small size, cameras are frequently used in localization applications where weight and power consumption are limiting factors, such as in the case of small-scale robots. Feature tracking based visual localization methods have poor performance in the abdomen region compared to outdoor or indoor large scale environments where unique features can be found easier

Objectives

Methods

Conclusion