Maximum contrast projection: A powerful tool for biomedical image stack analysis

Maximum intensity projection is a simple post-hoc dimension reduction approach that yields sharp 2-dimensional images from image stacks but is limited by low signal or high background. Herein, we demonstrated improvement in image contrast using maximum contrast versus maximum intensity projection in 3-dimensional phase-contrast and quantitative phase imaging of frozen cross-sections of murine peripheral nerve. Fresh frozen murine sciatic nerve sections were imaged using 3-dimensional fluorescence, phase-contrast, and quantitative phase microscopy. Images were processed using maximum intensity and maximum contrast projection. Higher image contrast of nerve morphology was obtained when the images were processed with maximum contrast projection. Enhanced image contrast in quantitative phase imaging facilitated label-free multicolor imaging of murine peripheral nerves. Herein, we demonstrate the utility of maximum contrast projection in enhancing image contrast over intensity projection approaches in fluorescence phase-contrast and quantitative phase imaging of nerve histological samples. A user-friendly, open-source Python-based maximum contrast projection algorithm to facilitate the adoption of this technique is provided.

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Publication Details

Journal
Journal of Neuropathology & Experimental Neurology
Published
2025-02-12
DOI
https://doi.org/10.1093/jnen/nlaf013
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Maximum contrast projection: A powerful tool for biomedical image stack analysis

Nate Jowett, Iván Coto Hernández, Andrew J. Link, Nat Adamian et al.
Journal of Neuropathology & Experimental Neurology
Cell Image Analysis Techniques
article

Maximum contrast projection: A powerful tool for biomedical image stack analysis

Nate Jowett, Iván Coto Hernández, Andrew J. Link, Nat Adamian, Christopher Guirguis
article en

Abstract

Maximum intensity projection is a simple post-hoc dimension reduction approach that yields sharp 2-dimensional images from image stacks but is limited by low signal or high background. Herein, we demonstrated improvement in image contrast using maximum contrast versus maximum intensity projection in 3-dimensional phase-contrast and quantitative phase imaging of frozen cross-sections of murine peripheral nerve. Fresh frozen murine sciatic nerve sections were imaged using 3-dimensional fluorescence, phase-contrast, and quantitative phase microscopy. Images were processed using maximum intensity and maximum contrast projection. Higher image contrast of nerve morphology was obtained when the images were processed with maximum contrast projection. Enhanced image contrast in quantitative phase imaging facilitated label-free multicolor imaging of murine peripheral nerves. Herein, we demonstrate the utility of maximum contrast projection in enhancing image contrast over intensity projection approaches in fluorescence phase-contrast and quantitative phase imaging of nerve histological samples. A user-friendly, open-source Python-based maximum contrast projection algorithm to facilitate the adoption of this technique is provided.

Journal of Neuropathology & Experimental NeurologyVol. 84(5)
Massachusetts Eye and Ear Infirmary (US), Harvard University (US)
U.S. Department of Defense, National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering
Openalex Percentile: Top 97%
Cell Image Analysis Techniques
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