[Video event 67] 3D image processing with scikit-image

[samvmdev]

Alex de Siqueira: 3D image processing with scikit-image

## Timestamps
00:00 Data Umbrella Introduction
03:38 Speaker Introduction - Alex de Siqueira
05:09 Introduction to scikit-image for 3D image analysis
06:05 What is scikit-image?
07:12 Checking the system 
07:39 Importing the base Scientific Python ecosystem (numpy, matplotlib, scipy)
08:29 Introduction to 3D image processing (grayscale v. multichannel)
10:25 Resolution within dimensions
11:14 Submodule + demo: skimage.io - utilities for reading and writing images
18:06 skimage.exposure - evaluating or changing the exposure of an image (reduce noise)
20:46 skimage.filters - apply filters to an image
22:57 skimage.transform - transforms & warping (downsampling example)
25:56 skimage.util - other utility functions
29:40 Thresholding - extract regions and see images (soft v. hard thresholding)
31:51 skimage.morphology - binary and grayscale morphology (use for improving image features)
33:36 skimage.measure - measuring image or region properties
37:53 skimage.feature - extract features from an image
38:45 skimage.segmentation - identification of regions of interest (supervised v. unsupervised)
47:21 Visualization
48:50 Going beyond - resources linked
50:27 Q&A - Segmentation and counting of objects
52:57 Q&A - Community calls for scikit-image
54:57 Q&A - Best way for people to get started
56:47 Q&A - Supported image formats
57:48 Q&A - Best way for community to get in touch, events (Hacktoberfest, PyData Global Online)

## Resources
ITK’s ikwidgets: https://github.com/InsightSoftwareConsortium/itkwidgets 

[reshamas]

@greenhacks Thank you.

1. The timestamps have been added to the video description.
2. The timestamps have been added to this file: https://github.com/data-umbrella/event-transcripts/blob/main/2022/67-alex-image.md
3. The checklist on the issue has been updated: https://github.com/data-umbrella/event-transcripts/issues/92

cc: @BerylKanali