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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 3: Hybrid Tracking and Matching Algorithm for Mosaicking Multiple Surgical Views
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Citations

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Chapter title
Hybrid Tracking and Matching Algorithm for Mosaicking Multiple Surgical Views
Chapter number 3
Book title
Computer-Assisted and Robotic Endoscopy
Published by
Springer, Cham, October 2016
DOI 10.1007/978-3-319-54057-3_3
Book ISBNs
978-3-31-954056-6, 978-3-31-954057-3
Authors

Chisato Takada, Toshiyuki Suzuki, Ahmed Afifi, Toshiya Nakaguchi, Takada, Chisato, Suzuki, Toshiyuki, Afifi, Ahmed, Nakaguchi, Toshiya

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 20%
Lecturer > Senior Lecturer 1 20%
Student > Master 1 20%
Unknown 2 40%
Readers by discipline Count As %
Earth and Planetary Sciences 1 20%
Medicine and Dentistry 1 20%
Unknown 3 60%

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