Buch, Englisch, 280 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g
Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics
4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings
Buch, Englisch, 280 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g
Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics
ISBN: 978-3-030-87601-2
Verlag: Springer International Publishing
The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.
*The workshop was held virtually.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs.- A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint.- One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction.- Mixing-AdaSIN: Constructing a De-biased Dataset using Adaptive Structural Instance Normalization and Texture Mixing.- Liver Tumor Localization and Characterization from Multi-Phase MR Volumes Using Key-Slice Prediction: A Physician-Inspired Approach.- Improving Tuberculosis Recognition on Bone-Suppressed Chest X-rays Guided by Task-Specific Features.- Template-Based Inter-modality Super-resolution of Brain Connectivity.- Adversarial Bayesian Optimization for Quantifying Motion Artifact within MRI.- False Positive Suppression in Cervical Cell Screening via Attention-Guided Semi-Supervised Learning.- Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine.- Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance.- Self-Guided Multi-Attention Network for Periventricular Leukomalacia Recognition.- Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray.- Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer.- Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network.- Probabilistic Deep Learning with Adversarial Training and Volume Interval Estimation – Better Ways to Perform and Evaluate Predictive Models for White Matter Hyperintensities Evolution.- A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis using Ultrasonography.- Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy using Multi-scale Patch Learning with Mammography.- The Pitfalls of SampleSelection: A Case Study on Lung Nodule Classification.- Anatomical Structure-aware Pulmonary Nodule Detection via Parallel Multi-Task RoI Head.- Towards Cancer Patients Classification Using Liquid Biopsy.- Foreseeing Survival through `Fuzzy Intelligence': A cognitively-inspired incremental learning based de novo model for Breast Cancer Prognosis by multi-omics data fusion.- Improving Across Dataset Brain Age Predictions using Transfer Learning.- Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation.- FLAT-Net: Longitudinal Brain Graph Evolution Prediction from a Few Training Representative Templates.
