Name | DL | Torrents | Total Size | Joe's Recommended Mirror List [edit] | 233 | 8.28TB | 1936 | 0 | Video Lectures [edit] | 155 | 727.63GB | 2855 | 0 |
medical-imaging-deep-learning-tutorial-2020 (7 files)
medical-imaging-deep-learning-tutorial-2020-slides.pdf | 7.74MB |
Medical Imaging Tutorial 2020 - Ch0 - Intro.mp4 | 4.82MB |
Medical Imaging Tutorial 2020 - Ch1 - Radiology and Multi-View.mp4 | 13.98MB |
Medical Imaging Tutorial 2020 - Ch2 - Histology and Segmentation.mp4 | 15.75MB |
Medical Imaging Tutorial 2020 - Ch3 - Cell Counting.mp4 | 10.11MB |
Medical Imaging Tutorial 2020 - Ch4 - Incorrect Feature Attribution.mp4 | 10.64MB |
Medical Imaging Tutorial 2020 - Ch5 - GANs in Medical Imaging.mp4 | 13.83MB |
Type: Course
Tags: radiology
Bibtex:
Tags: radiology
Bibtex:
@article{, title= {Medical Imaging with Deep Learning Tutorial 2020 - Joseph Paul Cohen}, keywords= {radiology}, author= {Joseph Paul Cohen}, abstract= {This tutorial will be styled as a graduate lecture about medical imaging with deep learning. This will cover the background of popular medical image domains (chest X-ray and histology) as well as methods to tackle multi-modality/view, segmentation, and counting tasks. These methods will be covered in terms of architecture and objective function design. Also, a discussion about incorrect feature attribution and approaches to mitigate the issue. Prerequisites: basic knowledge of computer vision (CNNs) and machine learning (regression, gradient descent). Presented by: Joseph Paul Cohen PhD Postdoctoral Fellow Mila, University of Montreal View presentations online here: https://www.youtube.com/playlist?list=PLheiZMDg_8ufxEx9cNVcOYXsT3BppJP4b https://i.imgur.com/0eexA1V.jpg https://i.imgur.com/GhTVcY0.jpg}, terms= {}, license= {https://creativecommons.org/licenses/by/4.0/}, superseded= {}, url= {https://www.youtube.com/playlist?list=PLheiZMDg_8ufxEx9cNVcOYXsT3BppJP4b} }