Generalist 3D Cell Phenotyping for All-Type Tissues

Tissue-clearing methods, light-sheet microscopy, and antibody labeling enable extracting cellular and subcellular information, producing large amount of image data needs to be analyzed. Hundreds of heterogeneous cell types were detected through the data obtained across species and types of tissues. We developed a novel approach that is generally applicable to a wide range of cell types in the large-scale 3D brain datasets, using a pipeline that performs accurate detection of cells regardless of image resolution, labeling pattern, and tissue processing techniques used. The pipeline is compatible with various labeling techniques including IHC, Fluorescence in situ hybridization (FISH), and genetic labeling and can be used for cellular level quantification in all types of tissues.

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

2021

Author dc:creator

• Gu, Xinyi

Advisor dc:contributor.advisor

• Chung, Kwanghun

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139887

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139887