Computer-Assisted and Robotic Endoscopy de Xiongbiao Luo

Computer-Assisted and Robotic Endoscopy: Lecture Notes in Computer Science, cartea 9515

Xiongbiao Luo

Tobias Reichl

Austin Reiter

Gian-Luca Mariottini

en Limba Engleză Paperback – 20 feb 2016

This book constitutes the thoroughly refereedpost-conference proceedings of the Second International Workshop on ComputerAssisted and Robotic Endoscopy, CARE 2015, held in conjunction with MICCAI2015, in Munich, Germany, in October 2015.
The 15 revised full papers were carefully selected out of20 initial submissions and focus on recent technical advances associated withcomputer vision; graphics; robotics and medical imaging; external trackingsystems; medical device control systems; information processing techniques;endoscopy; planning and simulation.

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Specificații

ISBN-13: 9783319299648
ISBN-10: 3319299646
Pagini: 180
Ilustrații: XII, 164 p. 91 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.28 kg
Ediția:1st edition 2016
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Impactof lossy image compression on CAD support systems for colonoscopy.- Pointingwith a One-Eyed Cursor for Supervised Training in Minimally Invasive RoboticSurgery.- Instrument Tracking with Rigid Part Mixtures Model.- A StereoscopicMotion Magnification in Minimally-Invasive Robotic Prostatectomy.- Tissue ShapeAcquisition with a Hybrid Structured Light and Photometric Stereo EndoscopicSystem.- Using Shading to Register an Intraoperative CT Scan to a LaparoscopicImage.- A Surgical Simulation Robot with Haptics and Friction Compensation.- AReal-Time Target Tracking Algorithm for a Robotic Flexible Endoscopy Platform.-2D/3D Real-Time Tracking of Surgical Instruments Based on Endoscopic ImageProcessing.- Tracking accuracy evaluation of electromagnetic sensor-basedcolonoscope tracking method.- Non Rigid Registration of 3D Images toLaparoscopic Video for Image Guided Surgery.- A novel dual Level Setscompetition model for colon region segmentation.- Enhancing Normal-AbnormalClassification Accuracy in Colonoscopy Videos via Consistency.- 3D StableSpatio-temporal Polyp Localization in Colonoscopy Videos.- Uninformative FrameDetection in Colonoscopy Through Motion, Edge and Color Features.