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This page lists fully automatic computer vision projects by Daniel Snider at the SickKids Research Institute in Toronto, Canada.

Segmentation in Transmission Electron Microscopy (TEM)

The green area is the glomerular basement membrane and each colored contour line is a podocyte foot process.

Project homepage: https://github.com/danielsnider/TEM-glomerular-basement-segmentation

Interaction of organelles inside single cells

Project homepage: https://github.com/danielsnider/peroxi_mito_analysis

3D Measurements of Pancreatic Islets

Project homepage: https://github.com/danielsnider/Cell-3D-Image-Analysis

Cell Size Variety in E-cadherin Immunofluorescence Histology Images

Project homepage: https://github.com/danielsnider/E-cadherin-Cell-Size

Track 2D cell motion and mitosis in time-lapse microscopy

Project homepage: https://github.com/danielsnider/Cell-Tracking

Growth of Intestinal Organoids

Project homepage: https://github.com/danielsnider/Growth-of-Intestinal-Organoids

Outlier Analysis

Investigating the trends seen in the localization of protein signal inside single cells. Hundreds of thousands of cells were segmented and we can choose to observe any sub-population.

Project homepage: https://github.com/danielsnider/Outlier-Analysis

Published Journal Article:

Anzi, Shira et al. (2018). Postnatal Exocrine Pancreas Growth by Cellular Hypertrophy Correlates with a Shorter Lifespan in Mammals. Developmental Cell, Volume 45, Issue 6, 726-737

Daniel contributed figures, statistics, and image analysis to the surprising discovery that acinar cell size is strongly correlated with animal life span.

Drawing

Journal Article: https://www.cell.com/developmental-cell/abstract/S1534-5807(18)30417-9

Full source code: https://github.com/danielsnider/E-cadherin-Cell-Size

Single Cell Analysis Toolkit

A GUI for nontechnical users to perform cell segmentation, measuring, tracking, and plotting of high-content screens.

Project homepage: https://github.com/danielsnider/Single_Cell_Analysis_Toolkit

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High throughput computer vision for cell biology research.

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