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Computer-Assisted and Robotic Endoscopy

Overview of attention for book
Cover of 'Computer-Assisted and Robotic Endoscopy'

Table of Contents

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    Book Overview
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    Chapter 1 Transfer Learning for Colonic Polyp Classification Using Off-the-Shelf CNN Features
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    Chapter 2 Probe Tracking and Its Application in Automatic Acquisition Using a Trans-Esophageal Ultrasound Robot
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    Chapter 3 Hybrid Tracking and Matching Algorithm for Mosaicking Multiple Surgical Views
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    Chapter 4 Assessment of Electromagnetic Tracking Accuracy for Endoscopic Ultrasound
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    Chapter 5 Extended Multi-resolution Local Patterns - A Discriminative Feature Learning Approach for Colonoscopy Image Classification
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    Chapter 6 Evaluation of i-Scan Virtual Chromoendoscopy and Traditional Chromoendoscopy for the Automated Diagnosis of Colonic Polyps
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    Chapter 7 ORBSLAM-Based Endoscope Tracking and 3D Reconstruction
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    Chapter 8 Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking
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    Chapter 9 Weakly-Supervised Lesion Detection in Video Capsule Endoscopy Based on a Bag-of-Colour Features Model
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    Chapter 10 Convolutional Neural Network Architectures for the Automated Diagnosis of Celiac Disease
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    Chapter 11 A System for Augmented Reality Guided Laparoscopic Tumour Resection with Quantitative Ex-vivo User Evaluation
Attention for Chapter 7: ORBSLAM-Based Endoscope Tracking and 3D Reconstruction
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Citations

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Chapter title
ORBSLAM-Based Endoscope Tracking and 3D Reconstruction
Chapter number 7
Book title
Computer-Assisted and Robotic Endoscopy
Published by
Springer, Cham, October 2016
DOI 10.1007/978-3-319-54057-3_7
Book ISBNs
978-3-31-954056-6, 978-3-31-954057-3
Authors

Nader Mahmoud, Iñigo Cirauqui, Alexandre Hostettler, Christophe Doignon, Luc Soler, Jacques Marescaux, J. M. M. Montiel, Mahmoud, Nader, Cirauqui, Iñigo, Hostettler, Alexandre, Doignon, Christophe, Soler, Luc, Marescaux, Jacques, Montiel, J. M. M.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 1%
Unknown 98 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 27%
Student > Master 16 16%
Researcher 12 12%
Student > Bachelor 5 5%
Professor 4 4%
Other 12 12%
Unknown 23 23%
Readers by discipline Count As %
Engineering 36 36%
Computer Science 24 24%
Medicine and Dentistry 6 6%
Unspecified 2 2%
Agricultural and Biological Sciences 1 1%
Other 6 6%
Unknown 24 24%

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