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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

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    Book Overview
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    Chapter 1 Improving Amide Proton Transfer-Weighted MRI Reconstruction Using T2-Weighted Images
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    Chapter 2 Compressive MR Fingerprinting Reconstruction with Neural Proximal Gradient Iterations
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    Chapter 3 Active MR k-space Sampling with Reinforcement Learning
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    Chapter 4 Fast Correction of Eddy-Current and Susceptibility-Induced Distortions Using Rotation-Invariant Contrasts
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    Chapter 5 Joint Reconstruction and Bias Field Correction for Undersampled MR Imaging
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    Chapter 6 Joint Total Variation ESTATICS for Robust Multi-parameter Mapping
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    Chapter 7 End-to-End Variational Networks for Accelerated MRI Reconstruction
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    Chapter 8 3d-SMRnet: Achieving a New Quality of MPI System Matrix Recovery by Deep Learning
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    Chapter 9 MRI Image Reconstruction via Learning Optimization Using Neural ODEs
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    Chapter 10 An Evolutionary Framework for Microstructure-Sensitive Generalized Diffusion Gradient Waveforms
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    Chapter 11 Lesion Mask-Based Simultaneous Synthesis of Anatomic and Molecular MR Images Using a GAN
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    Chapter 12 T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions
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    Chapter 13 Learned Proximal Networks for Quantitative Susceptibility Mapping
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    Chapter 14 Learning a Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction
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    Chapter 15 Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography
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    Chapter 16 Acceleration of High-Resolution 3D MR Fingerprinting via a Graph Convolutional Network
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    Chapter 17 Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness
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    Chapter 18 Learning MRI k-Space Subsampling Pattern Using Progressive Weight Pruning
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    Chapter 19 Model-Driven Deep Attention Network for Ultra-fast Compressive Sensing MRI Guided by Cross-contrast MR Image
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    Chapter 20 Simultaneous Estimation of X-Ray Back-Scatter and Forward-Scatter Using Multi-task Learning
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    Chapter 21 MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response
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    Chapter 22 $$\text {M}^2\text {Net}$$: Multi-modal Multi-channel Network for Overall Survival Time Prediction of Brain Tumor Patients
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    Chapter 23 Automatic Detection of Free Intra-abdominal Air in Computed Tomography
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    Chapter 24 Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Deep Learning with Integrative Imaging, Molecular and Demographic Data
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    Chapter 25 Geodesically Smoothed Tensor Features for Pulmonary Hypertension Prognosis Using the Heart and Surrounding Tissues
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    Chapter 26 Ovarian Cancer Prediction in Proteomic Data Using Stacked Asymmetric Convolution
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    Chapter 27 DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging
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    Chapter 28 Holistic Analysis of Abdominal CT for Predicting the Grade of Dysplasia of Pancreatic Lesions
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    Chapter 29 Feature-Enhanced Graph Networks for Genetic Mutational Prediction Using Histopathological Images in Colon Cancer
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    Chapter 30 Spatial-And-Context Aware (SpACe) “Virtual Biopsy” Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI
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    Chapter 31 CorrSigNet: Learning CORRelated Prostate Cancer SIGnatures from Radiology and Pathology Images for Improved Computer Aided Diagnosis
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    Chapter 32 Preoperative Prediction of Lymph Node Metastasis from Clinical DCE MRI of the Primary Breast Tumor Using a 4D CNN
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    Chapter 33 Learning Differential Diagnosis of Skin Conditions with Co-occurrence Supervision Using Graph Convolutional Networks
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    Chapter 34 Unified Cross-Modality Feature Disentangler for Unsupervised Multi-domain MRI Abdomen Organs Segmentation
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    Chapter 35 Dynamic Memory to Alleviate Catastrophic Forgetting in Continuous Learning Settings
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    Chapter 36 Unlearning Scanner Bias for MRI Harmonisation
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    Chapter 37 Cross-domain Medical Image Translation by Shared Latent Gaussian Mixture Model
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    Chapter 38 Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy
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    Chapter 39 X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph
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    Chapter 40 Domain Adaptation for Ultrasound Beamforming
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    Chapter 41 CDF-Net: Cross-Domain Fusion Network for Accelerated MRI Reconstruction
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    Chapter 42 Improve Unseen Domain Generalization via Enhanced Local Color Transformation
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    Chapter 43 Transport-Based Joint Distribution Alignment for Multi-site Autism Spectrum Disorder Diagnosis Using Resting-State fMRI
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    Chapter 44 Automatic and Interpretable Model for Periodontitis Diagnosis in Panoramic Radiographs
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    Chapter 45 Residual-CycleGAN Based Camera Adaptation for Robust Diabetic Retinopathy Screening
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    Chapter 46 Shape-Aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains
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    Chapter 47 Automatic Plane Adjustment of Orthopedic Intraoperative Flat Panel Detector CT-Volumes
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    Chapter 48 Unsupervised Graph Domain Adaptation for Neurodevelopmental Disorders Diagnosis
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    Chapter 49 JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering
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    Chapter 50 MI$$^2$$GAN: Generative Adversarial Network for Medical Image Domain Adaptation Using Mutual Information Constraint
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    Chapter 51 Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment
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    Chapter 52 Domain-Specific Loss Design for Unsupervised Physical Training: A New Approach to Modeling Medical ML Solutions
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    Chapter 53 Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect
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    Chapter 54 Chest X-Ray Report Generation Through Fine-Grained Label Learning
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    Chapter 55 Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time
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    Chapter 56 A Deep Bayesian Video Analysis Framework: Towards a More Robust Estimation of Ejection Fraction
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    Chapter 57 Distractor-Aware Neuron Intrinsic Learning for Generic 2D Medical Image Classifications
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    Chapter 58 Large-Scale Inference of Liver Fat with Neural Networks on UK Biobank Body MRI
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    Chapter 59 BUNET: Blind Medical Image Segmentation Based on Secure UNET
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    Chapter 60 Temporal-Consistent Segmentation of Echocardiography with Co-learning from Appearance and Shape
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    Chapter 61 Decision Support for Intoxication Prediction Using Graph Convolutional Networks
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    Chapter 62 Latent-Graph Learning for Disease Prediction
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    Chapter 63 BR-GAN: Bilateral Residual Generating Adversarial Network for Mammogram Classification
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    Chapter 64 Cycle Structure and Illumination Constrained GAN for Medical Image Enhancement
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    Chapter 65 Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GAN
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    Chapter 66 GANDALF: Generative Adversarial Networks with Discriminator-Adaptive Loss Fine-Tuning for Alzheimer’s Disease Diagnosis from MRI
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    Chapter 67 Brain MR to PET Synthesis via Bidirectional Generative Adversarial Network
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    Chapter 68 AGAN: An Anatomy Corrector Conditional Generative Adversarial Network
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    Chapter 69 SteGANomaly: Inhibiting CycleGAN Steganography for Unsupervised Anomaly Detection in Brain MRI
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    Chapter 70 Flow-Based Deformation Guidance for Unpaired Multi-contrast MRI Image-to-Image Translation
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    Chapter 72 Spatial-Intensity Transform GANs for High Fidelity Medical Image-to-Image Translation
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    Chapter 73 Graded Image Generation Using Stratified CycleGAN
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    Chapter 74 Prediction of Plantar Shear Stress Distribution by Conditional GAN with Attention Mechanism
Attention for Chapter 54: Chest X-Ray Report Generation Through Fine-Grained Label Learning
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Chapter title
Chest X-Ray Report Generation Through Fine-Grained Label Learning
Chapter number 54
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-59713-9_54
Book ISBNs
978-3-03-059712-2, 978-3-03-059713-9
Authors

Tanveer Syeda-Mahmood, Ken C. L. Wong, Yaniv Gur, Joy T. Wu, Ashutosh Jadhav, Satyananda Kashyap, Alexandros Karargyris, Anup Pillai, Arjun Sharma, Ali Bin Syed, Orest Boyko, Mehdi Moradi, Syeda-Mahmood, Tanveer, Wong, Ken C. L., Gur, Yaniv, Wu, Joy T., Jadhav, Ashutosh, Kashyap, Satyananda, Karargyris, Alexandros, Pillai, Anup, Sharma, Arjun, Syed, Ali Bin, Boyko, Orest, Moradi, Mehdi

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Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 17%
Student > Ph. D. Student 6 15%
Student > Bachelor 5 12%
Researcher 4 10%
Student > Doctoral Student 2 5%
Other 6 15%
Unknown 11 27%
Readers by discipline Count As %
Computer Science 17 41%
Engineering 5 12%
Chemistry 2 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Philosophy 1 2%
Other 2 5%
Unknown 13 32%