activity
20162022
most citedDeep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots

138 citations · 296 across the 12 of their papers we have counts for

collaborators
Showing 2017Show all

7 papers · 1 filter

cs.RO2017

EndoSensorFusion: Particle Filtering-Based Multi-sensory Data Fusion with Switching State-Space Model for Endoscopic Capsule Robots

Mehmet Turan, Yasin Almalioglu, Hunter Gilbert +3

A reliable, real time multi-sensor fusion functionality is crucial for localization of actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagn…

cs.CV2017

3D Reconstruction with Low Resolution, Small Baseline and High Radial Distortion Stereo Images

Tiago Dias, Helder Araujo, Pedro Miraldo

In this paper we analyze and compare approaches for 3D reconstruction from low-resolution (250x250), high radial distortion stereo images, which are acquired with small baseline (a…

cs.CV2017★ 138 cited

Deep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots

Mehmet Turan, Yasin Almalioglu, Helder Araujo +2

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologi…

cs.CV2017★ 36 cited

Sparse-then-Dense Alignment based 3D Map Reconstruction Method for Endoscopic Capsule Robots

Mehmet Turan, Yusuf Yigit Pilavci, Ipek Ganiyusufoglu +3

Since the development of capsule endoscopcy technology, substantial progress were made in converting passive capsule endoscopes to robotic active capsule endoscopes which can be co…

cs.CV2017★ 20 cited

A fully dense and globally consistent 3D map reconstruction approach for GI tract to enhance therapeutic relevance of the endoscopic capsule robot

Mehmet Turan, Yusuf Yigit Pilavci, Redhwan Jamiruddin +3

In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI…

cs.CV2017★ 61 cited

A Non-Rigid Map Fusion-Based RGB-Depth SLAM Method for Endoscopic Capsule Robots

Mehmet Turan, Yasin Almalioglu, Helder Araujo +2

In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is considered as a minimally invasive novel diagnostic technology to inspect the entire GI…

cs.CV2017★ 9 cited

Magnetic-Visual Sensor Fusion based Medical SLAM for Endoscopic Capsule Robot

Mehmet Turan, Yasin Almalioglu, Hunter Gilbert +3

A reliable, real-time simultaneous localization and mapping (SLAM) method is crucial for the navigation of actively controlled capsule endoscopy robots. These robots are an emergin…