Online histostereometric analysis in digital forensic pathology: a technical report

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Abstract

BACKGROUND: Quantitative image analysis of histological, histochemical, and immunohistochemical specimens is an essential component of digital forensic pathology. However, the scarcity of commercial analysis software limits the widespread implementation of digital pathology principles, and thus objective histological diagnosis, in forensic medical examinations in Russia. This article presents a readily accessible online application for automated histostereometric image analysis of histological and immunohistochemical specimens, as well as digital photographs of individual fields of view.

AIM: The work aimed to develop an online tool for histostereometric analysis of images used in digital forensic pathology.

METHODS: This work presents an online application compatible with Windows, Linux, Android, and iOS operating systems. The application is designed to detect microstructures with specific color characteristics in digital images and perform histostereometric analysis. The software code was written in JavaScript using the open-source library OpenCV.

RESULTS: An online application Color Histostereometry Calculator was developed to determine the relative volume and number of microstructures with specific color characteristics in raster images of histological and immunohistochemical specimens. The application uses the HSV (Hue, Saturation, Value) color model, with the ability to adjust the ranges of color parameters and the minimum size of the analyzed regions; moreover, it identifies microstructures based on their color characteristics rather than geometric features. This allows for the exclusion of various image artifacts from the analysis, the segmentation of overlapping structures, and the evaluation of morphometric parameters for an infinitesimally thin section, thereby eliminating the influence of section thickness on the analysis results.

CONCLUSION: The proposed online application is recommended for histostereometric analysis in digital forensic pathology.

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About the authors

Vladimir G. Nedugiv

Samara State Medical University

Author for correspondence.
Email: nedugovvg@gmail.com
ORCID iD: 0009-0007-7542-7235
SPIN-code: 2407-7937
Russian Federation, Samara

Anna V. Zhukova

Samara National Research University (Samara University)

Email: anna.zhuk.dreamer@yandex.ru
ORCID iD: 0009-0004-5237-7739
Russian Federation, Samara

German V. Nedugov

Samara National Research University (Samara University)

Email: nedugovh@mail.ru
ORCID iD: 0000-0002-7380-3766
SPIN-code: 3828-8091

MD, Dr. Sci. (Medicine), Assistant Professor

Russian Federation, Samara

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Supplementary files

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2. Fig. 1. Determination of the relative volume of hemosiderosis of the subdural hematoma capsule using the developed online application: a — original image; b — original image with the selection of hemosiderosis zones; c — black and white image mask.

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3. Fig. 2. Determination of the number of myeloid element nuclear profiles in a digital image of fetal liver using the developed online application: a — original image; b — original image with the selection of the contours of the nuclei located in focus (the image is presented in black and white for better contrast of the contours); c — black and white image mask.

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СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия ПИ № ФС 77 - 81753 выдано 09.09.2021 г. 
СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
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