Preanalytic variable effects on segmentation and quantification machine learning algorithms for amyloid-β analyses on digitized human brain slides-Reference-Cited by-同舟云学术

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Preanalytic variable effects on segmentation and quantification machine learning algorithms for amyloid-β analyses on digitized human brain slides

Published:2023-01-24 Issue:3 Volume:82 Page:212-220
ISSN:0022-3069
Container-title:Journal of Neuropathology & Experimental Neurology
language:en
Short-container-title:

Author:

Oliveira Luca Cerny,Lai Zhengfeng,Harvey Danielle,Nzenkue Kevin,Jin Lee-Way,Decarli Charles,Chuah Chen-Nee,Dugger Brittany N

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Neurology (clinical),Neurology,General Medicine,Pathology and Forensic Medicine

Link

https://academic.oup.com/jnen/article-pdf/82/3/212/49283719/nlac132.pdf

Reference26 articles.

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2. QuPath: Open source software for digital pathology image analysis;Bankhead;Sci Rep,2017

3. Pathology of neurodegenerative diseases;Dugger;Cold Spring Harb Perspect Biol,2017

4. Advances in deep neuropathological phenotyping of Alzheimer disease: Past, present, and future;Shakir;J Neuropathol Exp Neurol,2022

5. Interpretable deep learning of myelin histopathology in age-related cognitive impairment;McKenzie;Acta Neuropathol Commun,2022

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1. Optimization of whole slide imaging scan settings for computer vision using human lung cancer tissue;PLOS ONE;2024-09-09

2. Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases;Acta Neuropathologica Communications;2024-08-17

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4. Toward a generalizable machine learning workflow for neurodegenerative disease staging with focus on neurofibrillary tangles;Acta Neuropathologica Communications;2023-12-18

5. High-throughput digital quantification of Alzheimer disease pathology and associated infrastructure in large autopsy studies;Journal of Neuropathology & Experimental Neurology;2023-11-07

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