Pseudo-spectral angle mapping to improve immune cell classification in highly multiplexed fluorescence microscopy images

Madeleine S. Durkee; Junting Ai; Gabriel Casella; Thao Cao; Marcus R. Clark; Maryellen L. Giger

doi:10.1117/12.3003486

12 March 2024 Pseudo-spectral angle mapping to improve immune cell classification in highly multiplexed fluorescence microscopy images

Madeleine S. Durkee, Junting Ai, Gabriel Casella, Thao Cao, Marcus R. Clark, Maryellen L. Giger

Author Affiliations +

Proceedings Volume 12846, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXII; 1284603 (2024) https://doi.org/10.1117/12.3003486
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Highly multiplexed fluorescence microscopy is an emerging technology that allows for spatial analysis of increasingly more classes of cells within human tissue—state-of-the-art methods are now probing up to 60 different protein markers within an image. This level of phenotypic resolution is ideal for uncovering the spatial underpinnings of immune cell interactions. However, defining cell types from this high-plex data is non-trivial. We present a method that borrows from hyperspectral image analysis to improve the accuracy and efficiency of immune cell classification in highly multiplexed fluorescence microscopy images. Treating the protein marker image channels as the spectral dimension of the images, we define reference “pseudospectra” representative of the ideal marker expression for all cell types of interest probed by the marker panel. Cosine similarity is computed for each reference pseudo-spectra to create class maps for each cell type in question. Features are extracted from these class maps—rather than the fluorescence images. We compare these methods to a decision-tree based classification method for classifying immune cells and unsupervised K-means clustering of mean pixel intensities across all image channels. We demonstrate that pSAM performs comparably, and potentially outperforms methods with similar levels of supervision.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Madeleine S. Durkee, Junting Ai, Gabriel Casella, Thao Cao, Marcus R. Clark, and Maryellen L. Giger "Pseudo-spectral angle mapping to improve immune cell classification in highly multiplexed fluorescence microscopy images", Proc. SPIE 12846, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXII, 1284603 (12 March 2024); https://doi.org/10.1117/12.3003486

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available