Image Reconstruction Courses and Certifications

Modeling Prior Information to Guide Image Reconstruction in Radiation Therapy

Explore innovative techniques for incorporating prior knowledge into image reconstruction algorithms, enhancing accuracy and efficiency in radiation therapy planning and delivery.

• YouTube
• 22 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

The Role of Data and Models for Deep-Learning Based Image Reconstruction

Explores deep learning in image reconstruction, focusing on model scaling, data requirements, and robustness. Discusses performance under distribution shifts and strategies for improvement.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Geometric Understanding of Supervised and Unsupervised Deep Learning for Biomedical Image Reconstruction

Geometric understanding of deep learning for biomedical image reconstruction, exploring supervised and unsupervised approaches, with applications in various imaging modalities.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Deep Learning-Based MR Image Reconstruction and Contrast Conversion

Explore deep learning techniques for MR image reconstruction, parallel imaging, and contrast conversion, focusing on k-space and image space applications in medical imaging.

• YouTube
• 51 minutes
• On-Demand
• Free Video

INI Seminar Room 2

PaLEnTIR: A Parametric Level Set-based Approach to Image Reconstruction and Restoration

Discover a parametric level set-based approach to image reconstruction, focusing on efficient identification of regions of interest in medical imaging, hydrological data, and electromagnetic applications.

• YouTube
• 57 minutes
• On-Demand
• Free Video

Hausdorff Center for Mathematics

Solving Inverse Problems With Deep Neural Networks - Robustness Included?

Exploring robustness of deep learning in inverse problems, focusing on resilience against statistical noise and adversarial perturbations in image reconstruction tasks.

• YouTube
• 29 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Computational Microscopy: Coherent Diffractive Imaging to Electron Tomography

Explore computational microscopy techniques from coherent diffractive imaging to atomic electron tomography with UCLA expert Jianwei Miao in this insightful presentation on cutting-edge imaging methods.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Society for Industrial and Applied Mathematics

Self-supervised Deep Learning for Image Recovery - SIAM-IS Virtual Seminar

Self-supervised deep learning approach for image recovery, focusing on dataset-free methods. Explores Bayesian deep networks, uncertainty prediction, and applications in compressive sensing, outperforming traditional methods.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Society for Industrial and Applied Mathematics

Artifact Suppression in X-ray CT Images - SIAM-IS Virtual Seminar

Explore X-ray CT imaging, artifact suppression techniques, and recent advancements in metal and scattering artifact reduction for improved medical and industrial applications.

• YouTube
• 53 minutes
• On-Demand
• Free Video

Society for Industrial and Applied Mathematics

Convergence and Non-Convergence of Algebraic Iterative Reconstruction Methods - Imaging and Inverse Problems Seminar

Exploring convergence issues in algebraic iterative reconstruction methods for X-ray CT, presenting theoretical results and novel approaches to address non-convergence in limited-angle and limited-data scenarios.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Image Quality Evaluation of Deep Learning Image Reconstruction and Denoising in Clinical CT

Explore advanced techniques for assessing image quality in CT scans using deep learning, focusing on reconstruction and denoising methods for improved clinical outcomes.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Yannic Kilcher

Deep Image Reconstruction from Human Brain Activity

Explores innovative technique for reconstructing visual imagery from brain activity using fMRI and deep neural networks, demonstrating potential for "mind-reading" technology and insights into neural representations.

• YouTube
• 17 minutes
• On-Demand
• Free Video

Introduction to Deep Learning with Keras

25 ratings at DataCamp

Learn to start developing deep learning models with Keras.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

The Julia Programming Language

Tomographic Image Reconstruction with Julia

Explore Julia's capabilities for tomographic image reconstruction, focusing on large-scale inverse problems and matrix-free methods. Learn about package ecosystems for different imaging techniques.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Meta

New Approaches to Image and Video Reconstruction Using Deep Learning

Explore cutting-edge deep learning techniques for image and video enhancement, including colorization and resolution improvement, using efficient PyTorch-based tools trainable on a single GPU.

• YouTube
• 46 minutes
• On-Demand
• Free Video