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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

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Cover of 'Medical Image Computing and Computer Assisted Intervention – MICCAI 2020'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Lightweight Double Attention-Fused Networks for Intraoperative Stent Segmentation
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    Chapter 2 TopNet: Topology Preserving Metric Learning for Vessel Tree Reconstruction and Labelling
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    Chapter 3 Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction
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    Chapter 4 Branch-Aware Double DQN for Centerline Extraction in Coronary CT Angiography
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    Chapter 5 Automatic CAD-RADS Scoring Using Deep Learning
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    Chapter 6 Higher-Order Flux with Spherical Harmonics Transform for Vascular Analysis
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    Chapter 7 Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network
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    Chapter 8 Automated Intracranial Artery Labeling Using a Graph Neural Network and Hierarchical Refinement
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    Chapter 9 Time Matters: Handling Spatio-Temporal Perfusion Information for Automated TICI Scoring
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    Chapter 10 ID-Fit: Intra-Saccular Device Adjustment for Personalized Cerebral Aneurysm Treatment
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    Chapter 11 JointVesselNet: Joint Volume-Projection Convolutional Embedding Networks for 3D Cerebrovascular Segmentation
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    Chapter 12 Classification of Retinal Vessels into Artery-Vein in OCT Angiography Guided by Fundus Images
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    Chapter 13 Vascular Surface Segmentation for Intracranial Aneurysm Isolation and Quantification
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    Chapter 14 Deep Doubly Supervised Transfer Network for Diagnosis of Breast Cancer with Imbalanced Ultrasound Imaging Modalities
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    Chapter 15 2D X-Ray Mammogram and 3D Breast MRI Registration
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    Chapter 16 A Second-Order Subregion Pooling Network for Breast Lesion Segmentation in Ultrasound
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    Chapter 17 Multi-scale Gradational-Order Fusion Framework for Breast Lesions Classification Using Ultrasound Images
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    Chapter 18 Computer-Aided Tumor Diagnosis in Automated Breast Ultrasound Using 3D Detection Network
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    Chapter 19 Auto-weighting for Breast Cancer Classification in Multimodal Ultrasound
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    Chapter 20 MommiNet: Mammographic Multi-view Mass Identification Networks
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    Chapter 21 Multi-site Evaluation of a Study-Level Classifier for Mammography Using Deep Learning
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    Chapter 22 The Case of Missed Cancers: Applying AI as a Radiologist’s Safety Net
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    Chapter 23 Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models
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    Chapter 24 Multi-task Learning for Detection and Classification of Cancer in Screening Mammography
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    Chapter 25 Adaptive Context Selection for Polyp Segmentation
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    Chapter 26 PraNet: Parallel Reverse Attention Network for Polyp Segmentation
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    Chapter 27 Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy
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    Chapter 28 PolypSeg: An Efficient Context-Aware Network for Polyp Segmentation from Colonoscopy Videos
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    Chapter 29 Endoscopic Polyp Segmentation Using a Hybrid 2D/3D CNN
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    Chapter 30 A Distance-Based Loss for Smooth and Continuous Skin Layer Segmentation in Optoacoustic Images
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    Chapter 31 Fairness of Classifiers Across Skin Tones in Dermatology
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    Chapter 32 Alleviating the Incompatibility Between Cross Entropy Loss and Episode Training for Few-Shot Skin Disease Classification
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    Chapter 33 Clinical-Inspired Network for Skin Lesion Recognition
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    Chapter 34 Multi-class Skin Lesion Segmentation for Cutaneous T-cell Lymphomas on High-Resolution Clinical Images
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    Chapter 35 Deep Learning Automatic Fetal Structures Segmentation in MRI Scans with Few Annotated Datasets
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    Chapter 36 Data-Driven Multi-contrast Spectral Microstructure Imaging with InSpect
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    Chapter 37 Semi-supervised Learning for Fetal Brain MRI Quality Assessment with ROI Consistency
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    Chapter 38 Enhanced Detection of Fetal Pose in 3D MRI by Deep Reinforcement Learning with Physical Structure Priors on Anatomy
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    Chapter 39 Automatic Angle of Progress Measurement of Intrapartum Transperineal Ultrasound Image with Deep Learning
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    Chapter 40 Joint Image Quality Assessment and Brain Extraction of Fetal MRI Using Deep Learning
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    Chapter 41 Accelerated 4D Respiratory Motion-Resolved Cardiac MRI with a Model-Based Variational Network
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    Chapter 42 Motion Pyramid Networks for Accurate and Efficient Cardiac Motion Estimation
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    Chapter 43 ICA-UNet: ICA Inspired Statistical UNet for Real-Time 3D Cardiac Cine MRI Segmentation
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    Chapter 44 A Bottom-Up Approach for Real-Time Mitral Valve Annulus Modeling on 3D Echo Images
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    Chapter 45 A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography
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    Chapter 46 Joint Data Imputation and Mechanistic Modelling for Simulating Heart-Brain Interactions in Incomplete Datasets
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    Chapter 47 Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction
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    Chapter 48 Hierarchical Classification of Pulmonary Lesions: A Large-Scale Radio-Pathomics Study
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    Chapter 49 Learning Tumor Growth via Follow-Up Volume Prediction for Lung Nodules
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    Chapter 50 Multi-stream Progressive Up-Sampling Network for Dense CT Image Reconstruction
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    Chapter 51 Abnormality Detection in Chest X-Ray Images Using Uncertainty Prediction Autoencoders
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    Chapter 52 Region Proposals for Saliency Map Refinement for Weakly-Supervised Disease Localisation and Classification
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    Chapter 53 CPM-Net: A 3D Center-Points Matching Network for Pulmonary Nodule Detection in CT Scans
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    Chapter 54 Interpretable Identification of Interstitial Lung Disease (ILD) Associated Findings from CT
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    Chapter 55 Learning with Sure Data for Nodule-Level Lung Cancer Prediction
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    Chapter 56 Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation
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    Chapter 57 Class-Aware Multi-window Adversarial Lung Nodule Synthesis Conditioned on Semantic Features
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    Chapter 58 Nodule2vec: A 3D Deep Learning System for Pulmonary Nodule Retrieval Using Semantic Representation
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    Chapter 59 Deep Active Learning for Effective Pulmonary Nodule Detection
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    Chapter 60 Towards Robust Bone Age Assessment: Rethinking Label Noise and Ambiguity
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    Chapter 61 Improve Bone Age Assessment by Learning from Anatomical Local Regions
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    Chapter 62 An Analysis by Synthesis Method that Allows Accurate Spatial Modeling of Thickness of Cortical Bone from Clinical QCT
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    Chapter 63 Segmentation of Paraspinal Muscles at Varied Lumbar Spinal Levels by Explicit Saliency-Aware Learning
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    Chapter 64 Manifold Ordinal-Mixup for Ordered Classes in TW3-Based Bone Age Assessment
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    Chapter 65 Contour-Based Bone Axis Detection for X-Ray Guided Surgery on the Knee
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    Chapter 66 Automatic Segmentation, Localization, and Identification of Vertebrae in 3D CT Images Using Cascaded Convolutional Neural Networks
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    Chapter 67 Discriminative Dictionary-Embedded Network for Comprehensive Vertebrae Tumor Diagnosis
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    Chapter 68 Multi-vertebrae Segmentation from Arbitrary Spine MR Images Under Global View
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    Chapter 69 A Convolutional Approach to Vertebrae Detection and Labelling in Whole Spine MRI
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    Chapter 70 Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification
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    Chapter 71 Grading Loss: A Fracture Grade-Based Metric Loss for Vertebral Fracture Detection
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    Chapter 72 3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT
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    Chapter 73 SIMBA: Specific Identity Markers for Bone Age Assessment
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    Chapter 74 Doctor Imitator: A Graph-Based Bone Age Assessment Framework Using Hand Radiographs
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    Chapter 75 Inferring the 3D Standing Spine Posture from 2D Radiographs
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    Chapter 76 Generative Modelling of 3D In-Silico Spongiosa with Controllable Micro-structural Parameters
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    Chapter 77 GAN-Based Realistic Bone Ultrasound Image and Label Synthesis for Improved Segmentation
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    Chapter 78 Robust Bone Shadow Segmentation from 2D Ultrasound Through Task Decomposition
Attention for Chapter 22: The Case of Missed Cancers: Applying AI as a Radiologist’s Safety Net
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Chapter title
The Case of Missed Cancers: Applying AI as a Radiologist’s Safety Net
Chapter number 22
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-59725-2_22
Book ISBNs
978-3-03-059724-5, 978-3-03-059725-2
Authors

Michal Chorev, Yoel Shoshan, Adam Spiro, Shaked Naor, Alon Hazan, Vesna Barros, Iuliana Weinstein, Esma Herzel, Varda Shalev, Michal Guindy, Michal Rosen-Zvi, Chorev, Michal, Shoshan, Yoel, Akselrod-Ballin, Ayelet, Spiro, Adam, Naor, Shaked, Hazan, Alon, Barros, Vesna, Weinstein, Iuliana, Herzel, Esma, Shalev, Varda, Guindy, Michal, Rosen-Zvi, Michal

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Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 17%
Student > Ph. D. Student 2 17%
Professor > Associate Professor 2 17%
Student > Bachelor 1 8%
Student > Master 1 8%
Other 0 0%
Unknown 4 33%
Readers by discipline Count As %
Unspecified 2 17%
Computer Science 2 17%
Nursing and Health Professions 1 8%
Biochemistry, Genetics and Molecular Biology 1 8%
Physics and Astronomy 1 8%
Other 1 8%
Unknown 4 33%

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