March 3, 2026Open Access

Polarimetric analysis of the Alzheimer’s pathology in excised mouse brain tissue

Key Points

Alzheimer's pathology shows significant changes in skewness and kurtosis values with age, indicating nuanced statistical behavior.
Skewness increased while kurtosis decreased as age progressed, suggesting alterations in brain tissue structure over time.
Analysis utilizes a large dataset of excised mouse brain tissue to explore the statistical properties of Alzheimer's pathology.
Findings highlight the potential for machine learning methods to enhance clinical diagnosis of Alzheimer's disease.

Abstract

From the higher-order statistics, we concluded that the mean and standard deviation remained constant across the ages. Skewness values were positive and increased as the age progressed, whereas kurtosis decreased with age. The large available dataset opens the possibility of implementing machine learning methods to assist clinical diagnosis in the future.

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Discussion

Authors

Gaurav Sharma

Jens Pahnke

Bernhard Roth

Journals

Journal of Biomedical Optics

Actions

Institutions

Oslo University Hospital

Leibniz University Hannover

References and Citations

Connected Papers

Building similarity graph...

Analyzing shared references across papers

Polarimetric analysis of the Alzheimer’s pathology in excised mouse brain tissue

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

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