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

138 citations · 282 across the 7 of their papers we have counts for

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cs.CV2019

A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation

Robin Brügger, Christian F. Baumgartner, Ender Konukoglu

One of the key drawbacks of 3D convolutional neural networks for segmentation is their memory footprint, which necessitates compromises in the network architecture in order to fit…

cs.CV2017

An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation

Christian F. Baumgartner, Lisa M. Koch, Marc Pollefeys +1

Accurate segmentation of the heart is an important step towards evaluating cardiac function. In this paper, we present a fully automated framework for segmentation of the left (LV)…

cs.CV2017138 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.CV201736 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.CV201720 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.CV201761 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…