Medical Imaging with Deep Learning Tutorial 2020 - Joseph Paul Cohen

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

本教程将仿照研究生讲座的形式，深入探讨深度学习在医学影像领域的应用。讲座内容将涵盖流行医学影像领域（如胸部X光和病理学）的背景知识，以及处理多模态/视图、分割和计数任务的策略。这些策略将围绕架构设计和目标函数设计进行阐述。此外，还将讨论错误特征归因的问题及其缓解方法。先决条件：具备计算机视觉（卷积神经网络）和机器学习（回归、梯度下降）的基本知识。主讲人：Joseph Paul Cohen 博士，蒙特利尔大学Mila博士后。