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Deep Learning Image Restoration and Segmentation 1 (OSU 2024)

This video is a recording of the first workshop in a two-part series teaching practical skills in deep learning for image restoration and segmentation. The first part of the video is a seminar introducing deep learning for image restoration and segmentation. It is followed by a brief introduction to Python for beginners working with biomedical images. Finally, we walk through using csbdeep code for content-aware image restoration. These skills allow you to understand how to use Colab notebooks for performing image restoration and deep learning, allowing you to use code provided with publications and to have a deeper understanding of other Colab resources, such as those provided at ZerocostDL4mic: https://github.com/HenriquesLab/ZeroC... The example images and Colabs for following along with this workshop are provided below: https://drive.google.com/drive/folder... 0:00 Introduction 3:45 Machine learning 8:00 Example application 11:05 Deep learning 13:30 Image convolutions 17:30 U-Nets 21:10 Signal-to-noise 22:30 Applications of image restoration 30:00 Creating a training dataset 33:30 Introduction to Python for images 1:07:25 Content Aware Restoration CARE Colab 1:29:20 Image augmentation and CARE on an example dataset 1:45:20 ZeroCostDL4Mic