Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 : 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part II / 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, 12262

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12262

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, 785 pages) : 258 illustrations, 228 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:

Image Reconstruction

Improving Amide Proton Transfer-weighted MRI Reconstruction using T2-weighted Images

Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations

Active MR k-space Sampling with Reinforcement Learning

Fast Correction of Eddy-Current and Susceptibility-Induced Distortions Using Rotation-Invariant Contrasts

Joint reconstruction and bias field correction for undersampled MR imaging

Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping

End-to-End Variational Networks for Accelerated MRI Reconstruction

3d-SMRnet: Achieving a new quality of MPI system matrix recovery by deep learning

MRI Image Reconstruction via Learning Optimization Using Neural ODEs

An evolutionary framework for microstructure-sensitive generalized diffusion gradient waveforms

Lesion Mask-based Simultaneous Synthesis of Anatomic and Molecular MR Images using a GAN

T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions

Learned Proximal Networks for Quantitative Susceptibility Mapping

Learning A Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction

Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography

Acceleration of High-resolution 3D MR Fingerprinting via a Graph Convolutional Network

Deep Attentive Wasserstein Generative Adversarial Network for MRI Reconstruction with Recurrent Context-Awareness

Learning MRI $k$-Space Subsampling Pattern using Progressive Weight Pruning

Model-driven Deep Attention Network for Ultra-fast Compressive Sensing MRI Guided by Cross-contrast MR Image

Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning

Prediction and Diagnosis

MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response

M2Net: Multi-modal Multi-channel Network for Overall Survival Time Prediction of Brain Tumor Patients

Automatic Detection of Free Intra-Abdominal Air in Computed Tomography

Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Deep Learning with Integrative Imaging, Molecular and Demographic Data

Geodesically Smoothed Tensor Features for Pulmonary Hypertension Prognosis using the Heart and Surrounding Tissues

Ovarian Cancer Prediction in Proteomic Data Using Stacked Asymmetric Convolution

DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Dynamic Contrast-Enhanced CT Imaging

Holistic Analysis of Abdominal CT for Predicting the Grade of Dysplasia of Pancreatic Lesions

Feature-enhanced Graph Networks for Genetic Mutational Prediction Using Histopathological Images in Colon cancer

Spatial-And-Context aware (SpACe) "virtual biopsy'' radiogenomic maps to target tumor mutational status on structural MRI

CorrSigNet: Learning CORRelated Prostate Cancer SIGnatures from Radiology and Pathology Images for Improved Computer Aided Diagnosis

Preoperative prediction of lymph node metastasis from clinical DCE MRI of the primary breast tumor using a 4D CNN

Learning Differential Diagnosis of Skin Conditions with Co-occurrence Supervision using Graph Convolutional Networks

Cross-Domain Methods and Reconstruction

Unified cross-modality feature disentangler for unsupervised multi-domain MRI abdomen organs segmentation

Dynamic memory to alleviate catastrophic forgetting in continuous learning settings

Unlearning Scanner Bias for MRI Harmonisation

Cross-Domain Image Translation by Shared Latent Gaussian Mixture Model

Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy

X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph

Domain Adaptation for Ultrasound Beamforming

CDF-Net: Cross-Domain Fusion Network for accelerated MRI reconstruction

Domain Adaptation

Improve Unseen Domain Generalization via Enhanced Local Color Transformation and Augmentation

Transport-based Joint Distribution Alignment for Multi-site Autism Spectrum Disorder Diagnosis using Resting-state fMRI

Automatic and interpretable model for periodontitis diagnosis in panoramic radiographs

Residual-CycleGAN based Camera Adaptation for Robust Diabetic Retinopathy Screening

Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains

Automatic Plane Adjustment of Orthopedic Intraoperative Flat Panel Detector CT-Volumes

Unsupervised Graph Domain Adaptation for Neurodevelopmental Disorders Diagnosis

JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering

MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint

Machine Learning Applications

Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment

Domain-specific loss design for unsupervised physical training: A new approach to modeling medical ML solutions

Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect

Chest X-ray Report Generation through Fine-Grained Label Learning

Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time

A Deep Bayesian Video Analysis Framework: Towards a More Robust Estimation of Ejection Fraction

Distractor-Aware Neuron Intrinsic Learning for Generic 2D Medical Image Classifications

Large-scale inference of liver fat with neural networks on UK Biobank body MRI

BUNET: Blind Medical Image Segmentation Based on Secure UNET

Temporal-consistent Segmentation of Echocardiography with Co-learning from Appearance and Shape

Decision Support for Intoxication Prediction Using Graph Convolutional Networks

Latent-Graph Learning for Disease Prediction

Generative Adversarial Networks

BR-GAN: Bilateral Residual Generating Adversarial Network for Mammogram Classification

Cycle Structure and Illumination Constrained GAN for Medical Image Enhancement

Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GAN

GANDALF: Generative Adversarial Networks with Discriminator-Adaptive Loss Fine-tuning for Alzheimer's Disease Diagnosis from MRI

Brain MR to PET Synthesis via Bidirectional Generative Adversarial Network

AGAN: An Anatomy Corrector Conditional Generative Adversarial Network

SteGANomaly: Inhibiting CycleGAN Steganography for Unsupervised Anomaly Detection in Brain MRI

Flow-based Deformation Guidance for Unpaired Multi-Contrast MRI Image-to-Image Translation

Interpretation of Disease Evidence for Medical Images Using Adversarial Deformation Fields

Spatial-Intensity Transform GANs for High Fidelity Medical Image-to-Image Translation

Graded Image Generation Using Stratified CycleGAN

Prediction of Plantar Shear Stress Distribution by Conditional GAN with Attention Mechanism.

Other Format:

Printed edition:

ISBN:

978-3-030-59713-9

9783030597139

Access Restriction:

Restricted for use by site license.