000946555 000__ 11494cam\a2200625Ia\4500 000946555 001__ 946555 000946555 005__ 20230306152451.0 000946555 006__ m\\\\\o\\d\\\\\\\\ 000946555 007__ cr\un\nnnunnun 000946555 008__ 201031s2020\\\\sz\\\\\\o\\\\\101\0\eng\d 000946555 019__ $$a1202477912$$a1203979928$$a1224537500$$a1226041214$$a1226059076 000946555 020__ $$a9783030597139$$q(electronic book) 000946555 020__ $$a303059713X$$q(electronic book) 000946555 020__ $$z9783030597122 000946555 0247_ $$a10.1007/978-3-030-59713-9$$2doi 000946555 035__ $$aSP(OCoLC)on1202458332 000946555 035__ $$aSP(OCoLC)1202458332$$z(OCoLC)1202477912$$z(OCoLC)1203979928$$z(OCoLC)1224537500$$z(OCoLC)1226041214$$z(OCoLC)1226059076 000946555 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dDCT$$dSFB$$dGZM$$dOCLCO$$dEBLCP$$dOCLCF$$dUPM$$dERF$$dSNU 000946555 049__ $$aISEA 000946555 050_4 $$aRC78.7.D53 000946555 08204 $$a616.07/54$$223 000946555 1112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(23rd :$$d2020 :$$cOnline) 000946555 24510 $$aMedical image computing and computer assisted intervention -- MICCAI 2020 :$$b23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings.$$nPart II /$$cAnne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (eds.). 000946555 2463_ $$aMICCAI 2020 000946555 260__ $$aCham :$$bSpringer,$$c2020. 000946555 300__ $$a1 online resource (815 p.). 000946555 336__ $$atext$$btxt$$2rdacontent 000946555 337__ $$acomputer$$bc$$2rdamedia 000946555 338__ $$aonline resource$$bcr$$2rdacarrier 000946555 347__ $$atext file$$bPDF$$2rda 000946555 4901_ $$aLecture notes in computer science ;$$v12262 000946555 4901_ $$aLNCS sublibrary, SL 6, Image processing, computer vision, pattern recognition, and graphics 000946555 500__ $$aInternational conference proceedings. 000946555 500__ $$a"The conference was held through a virtual conference management platform, consisting of the main scientific program in addition to featuring 25 work-shops, 8 tutorials, and 24 challenges during October 4-8, 2020."-- Preface. 000946555 500__ $$aIncludes author index. 000946555 5050_ $$aImage 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. 000946555 506__ $$aAccess limited to authorized users. 000946555 520__ $$aThe 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 VII: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography. 000946555 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 2, 2020). 000946555 650_0 $$aDiagnostic imaging$$xData processing$$vCongresses. 000946555 7001_ $$aMartel, Anne. 000946555 7001_ $$aAbolmaesumi, Purang. 000946555 7001_ $$aStoyanov, Danail. 000946555 7001_ $$aMateus, Diana. 000946555 7001_ $$aZuluaga, Maria A. 000946555 7001_ $$aZhou, S. Kevin. 000946555 7001_ $$aRacoceanu, Daniel. 000946555 7001_ $$aJoskowicz, Leo. 000946555 77608 $$iPrint version:$$aMartel, Anne L.$$tMedical Image Computing and Computer Assisted Intervention - MICCAI 2020 : 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part II$$dCham : Springer International Publishing AG,c2020$$z9783030597122 000946555 830_0 $$aLecture notes in computer science ;$$v12262. 000946555 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics. 000946555 852__ $$bebk 000946555 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-59713-9$$zOnline Access$$91397441.1 000946555 909CO $$ooai:library.usi.edu:946555$$pGLOBAL_SET 000946555 980__ $$aEBOOK 000946555 980__ $$aBIB 000946555 982__ $$aEbook 000946555 983__ $$aOnline 000946555 994__ $$a92$$bISE