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Three dimensional visualization of histopathological data

Podwójcik Aleksandra

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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2023

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Vol. 27, No 1

1--11

EN

The histopathological examination provides information about the spatial assessment of pathological changes in the tissue. The authors present a method of extending this histopathological spatial assessment with a 3D view consisting of images of microscopic layers. The proposed solution creates 3D models based on images obtained from the database of the Medical University of Gdańsk (Digital Pathology). First, a series of medical images related to the study of a specific pathological tissue undergoes a process of background detection and removal through an algorithm. Next, images aligned with each other. Then, two types of 3D models are created: 1) classical model with Marching Cubes algorithm and 2) the use Cloud of Points.

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Computational methods for automated mitosis detection in histopathology images: A review

Mathew Tojo, Kini Jyoti R., Rajan Jeny

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 1

64--82

EN

Mitosis detection is an important step in pathology procedures in the context of cancer diagnosis and prognosis. Prevalent process for this task is by manually observing Hematox-ylin and Eosin (H & E) stained histopathology sections on glass slides through a microscope by trained pathologists. This conventional approach is tedious, error-prone, and has shown high inter-observer variability. With the advancement of computational technologies, automating mitosis detection by the use of image processing algorithms has attracted significant research interest. In the past decade, several methods appeared in the literature, addressing this problem and they have shown encouraging incremental progress towards a clinically usable solution. Mitosis count is an important parameter in grading of breast cancer and glioma, unlike other cancer types. Driven by the availability of multiple public datasets and open contests, most of the methods in literature address mitosis detection in breast cancer images. This paper is a comprehensive review of the methods published in the area of automated mitotic cell detection in H & E stained histopathology images of breast cancer in the last 10 years. We also discuss the current trends and future prospects of this clinically relevant task, augmenting humanity's fight against cancer.

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A review of current systems for annotation of cell and tissue images in digital pathology

Korzynska Anna, Roszkowiak Lukasz, Zak Jakub, Siemion Krzysztof

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 4

1436--1453

EN

With the advent and great advances of methods based on deep learning in image analysis, it appears that they can be effective in digital pathology to support the work of pathologists. However, a major limitation in the development of computer-aided diagnostic systems for pathology is the cost of data annotation. Evaluation of tissue (histopathological) and cellular (cytological) specimens seems to be a complex challenge. To simplify the laborious process of obtaining a sufficiently large set of data, a number of different systems could be used for image annotation. Some of these systems are reviewed in this paper with a comparison of their capabilities.

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MIAP – Web-based platform for the computer analysis of microscopic images to support the pathological diagnosis

Markiewicz T., Korzynska A., Kowalski A., Swiderska-Chadaj Z., Murawski P., Grala B., Lorent M., Wdowiak M., Zak J., Roszkowiak L., Kozlowski W., Pijanowska D.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

597--609

EN

The aim of the project is to design and to implement a web-based platform for the computer analysis of microscopic images which support the pathological diagnosis. The use of the platform will be free of charge. It offers: quantitative analysis of staining tissue sample' images, archiving microscopic images, peer consultation, and join work independently from distance between scientific collaborating centers to registered doctors, scientists and students. The use of proposed platform allows: (i) to save pathologists' time spend on quantitative analysis, (ii) to reduce consulting costs by replacing sending of the physical preparations by placing their images (mostly virtual slide) on the platform server, (iii) to increase reproducibility, comparability and objectivity of quantitative evaluations. These effects have a direct impact on improving the effectiveness and decreasing the costs of patients' treatment. This paper presents the main ideas of the project which deliver web-based system working as multi-functional, integrated, modular and scalable computer system. The details of hardware solutions, concept of the workflow in the platform, the programming language and interpreters, the specific tools and algorithms, and the user interfaces are described below. The practical solutions for web-based services in the area of medical image analysis, storage and retrieval are also presented and discussed.