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201103 ||| eng |
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|a 9783030597160
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|a Martel, Anne L.
|e [editor]
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|a Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
|h Elektronische Ressource
|b 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part III
|c edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
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|a 1st ed. 2020
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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|a XXXVI, 799 p. 23 illus
|b online resource
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|a Generliazing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration -- Instrumentation and Surgical Phase Detection -- TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks -- Surgical Video Motion Magnification with Suppression of Instrument Artefacts -- Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets -- AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation -- Automatic Operating Room Surgical Activity Recognition for Robot-Assisted Surgery -- Navigation and Visualization -- Can a hand-held navigation device reduce cognitive load? A user-centered approach evaluated by 18 surgeons -- Symmetric Dilated Convolution for Surgical Gesture Recognition -- Deep Selection: A Fully Supervised Camera Selection Network for Surgery Recordings -- Interacting with Medical Volume Data in Projective Augmented Reality --
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|a Towards Accurate and Interpretable Surgical Skill Assessment: A Video-Based Method Incorporating Recognized Surgical Gestures and Skill Levels -- Learning Motion Flows for Semi-supervised Instrument Segmentation from Robotic Surgical Video -- Spectral-Spatial Recurrent-Convolutional Networks for In-Vivo Hyperspectral Tumor Type Classification -- Synthetic and Real Inputs for Tool Segmentation in Robotic Surgery -- Perfusion Quantification from Endoscopic Videos: Learning to Read Tumour Signatures -- Asynchronous in Parallel Detection and Tracking (AIPDT): Real-time Robust Polyp Detection -- OfGAN: Realistic Rendition of Synthetic Colonoscopy Videos -- Two-Stream Deep Feature Modelling for Automated Video Endoscopy Data Analysis -- Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse Surgical Instrument Usage for Context-aware Assistance -- Deep Placental Vessel Segmentation for Fetoscopic Mosaicking --
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|a Deep Multi-View Stereo for Dense 3D Reconstruction from Monocular Endoscopic Video -- Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation
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|a Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound -- Contrastive Rendering for Ultrasound Image Segmentation -- An Unsupervised Approach to Ultrasound Elastography with End-to-end Strain Regularisation -- Automatic Probe Movement Guidance for Freehand Obstetric Ultrasound -- Video Image Analysis -- ISINet: An Instance-Based Approach for Surgical Instrument Segmentation -- Reliable Liver Fibrosis Assessment from Ultrasound using Global Hetero-Image Fusion and View-Specific Parameterization -- Toward Rapid Stroke Diagnosis with Multimodal Deep Learning -- Learning and Reasoning with the Graph Structure Representation in Robotic Surgery -- Vision-based Estimation of MDS-UPDRS Gait Scores for Assessing Parkinson's Disease Motor Severity -- Searching for Efficient Architecture for Instrument Segmentation in Robotic Surgery -- Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion --
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|a Unsupervised Learning Model for Registration of Multi-Phase Ultra-Widefield Fluorescein Angiography -- Large DeformationDiffeomorphic Image Registration with Laplacian Pyramid Networks -- Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration -- Cross-Modality Multi-Atlas Segmentation Using Deep Neural Networks -- Longitudinal Image Registration with Temporal-order and Subject-specificity Discrimination -- Flexible Bayesian Modelling for Nonlinear Image Registration -- Are Registration Uncertainty and Error Monotonically Associated? -- MR-to-US registration using multiclass segmentation of hepatic vasculature with a reduced 3D U-Net -- Detecting Pancreatic Ductal Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble -- Biomechanics-informed Neural Networks for Myocardial Motion Tracking in MRI -- Fluid registration between lung CT and stationary chest tomosynthesis images -- Anatomical Data Augmentation via Fluid-based Image Registration --
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|a Malocclusion Treatment Planning via PointNet based Spatial Transformation Network -- Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised Learning -- Local Contractive Registration for Quantification of Tissue Shrinkage in Assessment of Microwave Ablation -- Reinforcement Learning of Musculoskeletal Control from Functional Simulations -- Image Registration -- MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation -- Database Annotation with few Examples: An Atlas-based Framework using Diffeomorphic Registration of 3D trees -- Pair-wise and Group-wise Deformation Consistency in Deep Registration Network -- Semantic Hierarchy Guided Registration Networks for Intra-Subject Pulmonary CT Image Alignment -- Highly accurate and memory efficient unsupervised learning-based discrete CT registration using 2.5D displacement search --
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|a CAI Applications -- Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment -- Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee -- Feasibility check: can audio be a simple alternative to force-based feedback for needle guidance? -- A Graph-Based Method for Optimal Active Electrode Selection in Cochlear Implants -- Improved resection margins in surgical oncology using intraoperative mass spectrometry -- Self-Supervsied Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking -- An Interactive Mixed Reality Platform for Bedside Surgical Procedures -- Ear Cartilage Inference for Reconstructive Surgery with Convolutional Mesh Autoencoders -- Robust Multi-modal 3D Patient Body Modeling -- A New Electromagnetic-Video Endoscope Tracking Method via Anatomical Constraints and Historically Observed Differential Evolution --
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|a VR Simulation of Novel Hands-free Interaction Concepts for Surgical Robotic Visualization Systems -- Spatially-Aware Displays for Computer Assisted Interventions -- Ultrasound Imaging.-Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning -- Ultra2Speech - A Deep Learning Framework for Formant Frequency Estimation and Tracking from Ultrasound Tongue Images -- Ultrasound Video Summarization using Deep Reinforcement Learning -- Predicting obstructive hydronephrosis based on ultrasound alone -- Semi-Supervised Training of Optical Flow Convolutional Neural Networks in Ultrasound Elastography -- Three-dimensional thyroid assessment from untracked 2D ultrasound clips -- Complex Cancer Detector: Complex Neural Networks on Non-stationary Time Series for Guiding Systematic Prostate Biopsy -- Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound -- Directing Ultrasound Probe Placement for Image Guided Prostate Radiotherapy --
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|a Social sciences / Data processing
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|a Bioinformatics
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|a Computer Application in Social and Behavioral Sciences
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|a Computer Vision
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|a Computer vision
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|a Automated Pattern Recognition
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|a Education / Data processing
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|a Computers and Education
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|a Computational and Systems Biology
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|a Artificial Intelligence
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|a Pattern recognition systems
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|a Artificial intelligence
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700 |
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|a Abolmaesumi, Purang
|e [editor]
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700 |
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|a Stoyanov, Danail
|e [editor]
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|a Mateus, Diana
|e [editor]
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041 |
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7 |
|a eng
|2 ISO 639-2
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989 |
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|b Springer
|a Springer eBooks 2005-
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490 |
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics
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028 |
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|a 10.1007/978-3-030-59716-0
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|u https://doi.org/10.1007/978-3-030-59716-0?nosfx=y
|x Verlag
|3 Volltext
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|a 006.37
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|a The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography
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