| Name | DL | Torrents | Total Size | ||
| Joe's Recommended Mirror List [edit] | 233 | 8.28TB | 1717 | 0 | |
| Video Lectures [edit] | 155 | 727.63GB | 2296 | 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
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
URL: https://www.youtube.com/playlist?list=PLheiZMDg_8ufxEx9cNVcOYXsT3BppJP4b
License: https://creativecommons.org/licenses/by/4.0/
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
URL: https://www.youtube.com/playlist?list=PLheiZMDg_8ufxEx9cNVcOYXsT3BppJP4b
License: https://creativecommons.org/licenses/by/4.0/
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}
}
