Pipeline for semi-automatic segmentation of confluent endothelial cell membranes

Changes in cell morphology are important indicators of underlying biological changes. As endothelial cells (EC) heterogeneously respond to stimuli, we seek to quantify EC morphologic heterogeneity and relate it to transcriptome phenotypes; however, existing semi-automatic methods for quantifying cell shape require adjusting complex, non-linear hyperparameters by trial and error, making it difficult to attain the level of accuracy required to assess individual cell parameters. Manual segmentation, on the other hand, is not feasible for assessing heterogeneity because it requires segmentation of each individual cell. In this project, we tested two approaches to semi-automatic cell segmentation to improve both accuracy and speed. First, we built a tool that interfaces with Cell- Profiler, the current state-of-the-art cell segmentation software.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Ibarra, Sabrina Elizabeth.

Advisor dc:contributor.advisor

• Elazer R. Edelman.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/124249

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/124249