Predictive intelligence in medicine : third International Workshop, PRIME 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings

Predictive intelligence in medicine : third International Workshop, PRIME 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings / Islem Rekik, Ehsan Adeli, Sang Hyun Park, Maria del C. Valdés Hernández (eds.)

This book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually due to the COVID-19 pandemic. The 17 full and 2 short papers presented...

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Bibliographic Details
Corporate Authors: PRIME (Workshop) Online), International Conference on Medical Image Computing and Computer-Assisted Intervention
Other Authors: Rekik, Islem, Adeli, Ehsan, Park, Sang Hyun, Valdés Hernández, María
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2020]
Series:Lecture notes in computer science ; 12329.
LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics.
Subjects:
Artificial intelligence > Medical applications > Congresses.
Predictive analytics.
Artificial intelligence > Medical applications
Predictive analytics
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Table of Contents:
  • Intro
  • Preface
  • Organization
  • Contents
  • Context-Aware Synergetic Multiplex Network for Multi-organ Segmentation of Cervical Cancer MRI
  • 1 Introduction
  • 2 Proposed Context-Aware Synergetic Multiplex Network for Multi-organ Segmentation
  • 3 Results and Discussion
  • 4 Conclusion
  • References
  • Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation
  • 1 Introduction
  • 2 Proposed Method
  • 3 Results and Discussion
  • 4 Conclusion
  • References
  • Adversarial Brain Multiplex Prediction from a Single Network for High-Order Connectional Gender-Specific Brain Mapping
  • 1 Introduction
  • 2 Proposed Deep Brain Multiplex Prediction Using G-GAN for Gender Fingerprinting
  • 3 Results and Discussion
  • 4 Conclusion
  • References
  • Learned Deep Radiomics for Survival Analysis with Attention
  • 1 Introduction
  • 2 Related Work
  • 3 Method
  • 3.1 From Cox Survival Model to Loss Function
  • 3.2 CNN Model for Survival Analysis
  • 4 Experimental Validation
  • 4.1 Experiment 1. CNNs vs Classical Methods for Survival Analysis
  • 4.2 Experiment 2. Evaluation of Deep Learning Methods
  • 5 Discussion and Conclusions
  • References
  • Robustification of Segmentation Models Against Adversarial Perturbations in Medical Imaging
  • 1 Introduction
  • 2 Methodology
  • 3 Experiments
  • 4 Conclusion
  • References
  • Joint Clinical Data and CT Image Based Prognosis: A Case Study on Postoperative Pulmonary Venous Obstruction Prediction
  • 1 Introduction
  • 2 Methods
  • 2.1 Clinical Data Based Method
  • 2.2 CT Image Based Method
  • 2.3 Joint Data and Image Based Method
  • 3 Dataset
  • 4 Preprocessing and Learning Techniques
  • 4.1 Image Augmentation
  • 4.2 Resampling
  • 4.3 Loss Function Modification
  • 5 Experiments
  • 6 Conclusion
  • References
  • Low-Dose CT Denoising Using Octave Convolution with High and Low Frequency Bands
  • 1 Introduction
  • 1.1 Related Work
  • 2 Method
  • 3 Experimental Results
  • 3.1 Dataset and Experimental Settings
  • 3.2 Quantitative Results
  • 3.3 Qualitative Results
  • 4 Conclusions
  • References
  • Conditional Generative Adversarial Network for Predicting 3D Medical Images Affected by Alzheimer's Diseases
  • 1 Introduction
  • 2 Method
  • 2.1 Details of Proposed Network
  • 2.2 Objective Function
  • 3 Experimental Results
  • 4 Conclusion
  • References
  • Inpainting Cropped Diffusion MRI Using Deep Generative Models
  • 1 Introduction
  • 2 Methods
  • 2.1 Model Architecture
  • 2.2 Dataset and Evaluation Metrics
  • 3 Results and Discussion
  • 3.1 Evaluation on Artificially Cropped B0 MRIs of DWI
  • 3.2 Impact on Downstream Preprocessing
  • 4 Conclusion
  • References
  • Multi-view Brain HyperConnectome AutoEncoder for Brain State Classification
  • 1 Introduction
  • 2 Proposed HyperConnectome AutoEncoder (HCAE) for Brain State Classification
  • 3 Results and Discussion

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