Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 : 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VI / edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz.

Format:

Book

Contributor:

Martel, Anne L., Editor.

Abolmaesumi, Purang, Editor.

Stoyanov, Danail, Editor.

Mateus, Diana., Editor.

Zuluaga, Maria A., Editor.

Zhou, S. Kevin, Editor.

Racoceanu, Daniel, Editor.

Joskowicz, Leo., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12266

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12266

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Social sciences-Data processing.

Education-Data processing.

Pattern recognition systems.

Bioinformatics.

Computer Vision.

Artificial Intelligence.

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Automated Pattern Recognition.

Computational and Systems Biology.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Automated Pattern Recognition.

Computational and Systems Biology.

Physical Description:

1 online resource (XXXVII, 819 pages) : 33 illustrations, 1 illustrations in color.

Edition:

1st ed. 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

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.

Contents:

Angiography and Vessel Analysis

Lightweight Double Attention-fused Networks for Intraoperative Stent Segmentation

TopNet: Topology Preserving Metric Learning for Vessel Tree Reconstruction and Labelling

Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

Branch-aware Double DQN for Centerline Extraction in Coronary CT Angiography

Automatic CAD-RADS Scoring from CCTA Scans using Deep Learning

Higher-Order Flux with Spherical Harmonics Transform for Vascular Analysis

Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network

Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement

Time matters: Handling spatio-temporal perfusion information for automated TICI scoring

ID-Fit: Intra-saccular Device adjustment for personalized cerebral aneurysm treatment

JointVesselNet: Joint Volume-Projection Convolutional Embedding Networks for 3D Cerebrovascular Segmentation

Classification of Retinal Vessels into Artery-Vein in OCT Angiography Guided by Fundus Images

Vascular surface segmentation for intracranial aneurysm isolation and quantification

Breast Imaging

Deep Doubly Supervised Transfer Network for Diagnosis of Breast Cancer with Imbalanced Ultrasound Imaging Modalities

2D X-ray mammography and 3D breast MRI registration

A Second-order Subregion Pooling Network for Breast Ultrasound Lesion Segmentation

Multi-Scale Gradational-Order Fusion Framework for Breast lesions Classification Using Ultrasound images

Computer-aided Tumor Diagnosis in Automated Breast Ultrasound using 3D Detection Network

Auto-weighting for Breast Cancer Classification in Multimodal Ultrasound

MommiNet: Mammographic Multi-View Mass Identification Networks

Multi-Site Evaluation of a Study-Level Classifier for Mammography using Deep Learning

The case of missed cancers: Applying AI as a radiologist's safety net

Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models

Multi-task learning for detection and classification of cancer in screening mammography

Colonoscopy

Adaptive Context Selection for Polyp Segmentation

PraNet: Parallel Reverse Attention Network for Polyp Segmentation

Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy

PolypSeg: an Efficient Context-aware Network for Polyp Segmentation from Colonoscopy Videos

Endoscopic polyp segmentation using a hybrid 2D/3D CNN

Dermatology

A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images

Fairness of Classifiers Across Skin Tones in Dermatology

Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification

Clinical-Inspired Network for Skin Lesion Recognition

Multi-class Skin Lesion Segmentation for Cutaneous T-cell Lymphomas on High-Resolution Clinical Images

Fetal Imaging

Deep learning automatic fetal structures segmentation in MRI scans with few annotated datasets

Data-Driven Multi-Contrast Spectral Microstructure Imaging with InSpect

Semi-Supervised Learning for Fetal Brain MRI Quality Assessment with ROI consistency

Enhanced detection of fetal pose in 3D MRI by Deep Reinforcement Learning with physical structure priors on anatomy

Automatic angle of progress measurement of intrapartum transperineal ultrasound image with deep learning

Joint Image Quality Assessment and Brain Extraction of Fetal MRI using Deep Learning

Heart and Lung Imaging

Accelerated 4D Respiratory Motion-resolved Cardiac MRI with a Model-based Variational Network

Motion Pyramid Networks for Accurate and Efficient Cardiac Motion Estimation

ICA-UNet: ICA Inspired Statistical UNet for Real-time 3D Cardiac Cine MRI Segmentation

A Bottom-up Approach for Real-time Mitral Valve Annulus Modeling on 3D Echo Images

A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography

Joint data imputation and mechanistic modelling for simulating heart-brain interactions in incomplete datasets

Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction

Hierarchical Classification of Pulmonary Lesions: A Large-Scale Radio-Pathomics Study

Learning Tumor Growth via Follow-Up Volume Prediction for Lung Nodules

Multi-stream Progressive Up-sampling Network for Dense CT Image Reconstruction

Abnormality Detection in Chest X-ray Images Using Uncertainty Prediction Autoencoders

Region Proposals for Saliency Map Refinement for Weakly-supervised Disease Localisation and Classification

CPM-Net: A 3D Center-Points Matching Network for Pulmonary Nodule Detection in CT Scans

Interpretable Identification of Interstitial Lung Diseases (ILD) Associated Findings from CT

Learning with Sure Data for Nodule-Level Lung Cancer Prediction

Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation

Class-Aware Multi-Window Adversarial Lung Nodule Synthesis Conditioned on Semantic Features

Nodule2vec: a 3D Deep Learning System for Pulmonary Nodule Retrieval Using Semantic Representation

Deep Active Learning for Effective Pulmonary Nodule Detection

Musculoskeletal Imaging

Towards Robust Bone Age Assessment: Rethinking Label Noise and Ambiguity

Improve bone age assessment by learning from anatomical local regions

An Analysis by Synthesis Method that Allows Accurate Spatial Modeling of Thickness of Cortical Bone from Clinical QCT

Segmentation of Paraspinal Muscles at Varied Lumbar Spinal Levels by Explicit Saliency-Aware Learning

Manifold Ordinal-Mixup for Ordered Classes inTW3-based Bone Age Assessment

Contour-based Bone Axis Detection for X-Ray Guided Surgery on the Knee

Automatic Segmentation, Localization, and Identification of Vertebrae in 3D CT Images Using Cascaded Convolutional Neural Networks

Discriminative dictionary-embedded network for comprehensive vertebrae tumor diagnosis

Multi-vertebrae segmentation from arbitrary spine MR images under global view

A Convolutional Approach to Vertebrae Identification in Whole Spine MRI

Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification

Grading Loss: A Fracture Grade-based Metric Loss for Vertebral Fracture Detection

3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT

SIMBA: Specific Identity Markers for Bone Age Assessment

Doctor Imitator: A Graph-based Bone Age Assessment Framework Using Hand Radiographs

Inferring the 3D Standing Spine Posture from 2D Radiographs

Generative Modelling of 3D in-silico Spongiosa with Controllable Micro-Structural Parameters

GAN-based Realistic Bone Ultrasound Image and Label Synthesis for Improved Segmentation

Robust Bone Shadow Segmentation from 2D Ultrasound Through Task Decomposition.

Other Format:

Printed edition:

ISBN:

978-3-030-59725-2

9783030597252

Access Restriction:

Restricted for use by site license.