An Optimized and Advanced Algorithm for the Quantification of Immunohistochemical Biomarkers in Keratinocytes

JID innovations : skin science from molecules to population health Pub Date : 2024-05-01 DOI:10.1016/j.xjidi.2024.100270

Lindsey G. Siegfried , Sophie M. Bilik , Jamie L. Burgess , Paola Catanuto , Ivan Jozic , Irena Pastar , Rivka C. Stone , Marjana Tomic-Canic

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引用次数: 0

Abstract

Advancements in pathology have given rise to software applications intended to minimize human error and improve efficacy of image analysis. Still, the subjectivity of image quantification performed manually and the limitations of the most ubiquitous tissue stain analysis software requiring parameters tuned by the observer, reveal the need for a highly accurate, automated nuclear quantification software specific to immunohistochemistry, with improved precision and efficiency compared with the methods currently in use. We present a method for the quantification of immunohistochemical biomarkers in keratinocyte nuclei proposed to overcome these limitations, contributing sensitive shape-focused segmentation, accurate nuclear detection, and automated device-independent color assessment, without observer-dependent analysis parameters.

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用于量化角朊细胞免疫组化生物标记物的先进优化算法

病理学的发展催生了各种应用软件，旨在最大限度地减少人为误差，提高图像分析的效率。尽管如此，人工进行图像量化的主观性以及最普遍的组织染色分析软件要求观察者调整参数的局限性，都表明我们需要一种专门针对免疫组化的高精度、自动化核量化软件，与目前使用的方法相比，它能提高精确度和效率。我们提出了一种用于量化角朊细胞核中免疫组化生物标记物的方法，旨在克服这些局限性，提供灵敏的形状聚焦分割、准确的核检测和独立于设备的自动颜色评估，而无需依赖观察者的分析参数。

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来源期刊

JID innovations : skin science from molecules to population health Dermatology

CiteScore

4.00

自引率

0.00%

发文量

审稿时长

8 weeks