Unsupervised segmentation of complex tissue using multiplexed imaging-derived a priori knowledge

October 6, 2021

Conference

Unsupervised segmentation of complex tissue using multiplexed imaging-derived a priori knowledge

B. Kochetov, R. Raphael, S. Uttam

Biomedical Engineering Society (BMES) 2021 Annual Meeting (Oct 6 - 9, 2021; Orlando, Florida). Abstract 074 - 841, BMES 2021 Annual Meeting.

We present our preliminary results on a new unsupervised method we are developing for segmenting complex tissue samples in highly multiplexed immunofluorescence images.

More News

UNSEG, an easy to use unsupervised segmentation method for segmenting cells and their nuclei in complex tissue samples. It performs on par with current state-of-the-art deep learning methods while achieving improved internal consistency between cells and their nuclei

September 1, 2024

Bogdan and Rebecca are Microscopy Society of America's Micrograph Award Finalists!

August 1, 2024

Chan Zuckerberg Initiative grant award

July 24, 2024

Congratulations to Rajdeep for being accepted for a talk at ISCB GLBIO 2024!

March 29, 2024

Perspective on quantitative phase imaging to improve precision cancer medicine

March 29, 2024

Caitlin is a first year graduate student in the Joint CMU-Pitt Ph.D. Program in Computational Biology (CPCB). And she is a new member of the lab. Welcome Caitlin!

January 1, 2024

Thomas is a first year graduate student in the Joint CMU-Pitt Ph.D. Program in Computational Biology (CPCB). And he is a new member of the lab. Welcome Thomas!

January 1, 2024

Chris will be presenting his work on inferring cell communication from highly mulitplexed imaging of tissue microenvironments at CSHL Single Cell Analyses meeting

November 1, 2023