http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020
23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part III
1 online resource (XXXVI, 799 pages 23 illustrations)
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.
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 -- 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 -- Unsupervised Learning Model for Registration of Multi-Phase Ultra-Widefield Fluorescein Angiography -- Large Deformation Diffeomorphic 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 -- 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 -- 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 -- 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 -- 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 -- Deep Multi-View Stereo for Dense 3D Reconstruction from Monocular Endoscopic Video -- Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation.
edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz.
Computer Appl. in Social and Behavioral Sciences
Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12263