ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2020
A simple segmentation and quantification method for numerical quantitative analysis of cells and tissues.
Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Acellular Extracellular Matrix Scaffolds in Regenerative Medicine: Advances in Decellularization and Clinical Applications.Journal of functional biomaterials · 2025Review
- Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues.Scientific reports · 2022Article
- Image-Based Method to Quantify Decellularization of Tissue Sections.International journal of molecular sciences · 2021Article
- Semantic Segmentation of Intralobular and Extralobular Tissue from Liver Scaffold H&E Images.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
6 authors.
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Abstract
backgroundMicroscopic image analysis based on image processing is required for quantitative evaluation of decellularization. Existing methods are not widely used because of expensive commercial software, and machine learning-based techniques lack generality for decellularization because many high-resolution image data has to be processed.
objectiveIn this study, we developed an image processing algorithm for quantitative analysis of tissues and cells in a general microscopic image.
methodsThe proposed method extracts the color images obtained by the microscope into reference images consisting of grayscale, red (R), green (G), and blue (B) information and transforms each into a binary image. The transformed images were extracted by separating the cells and tissues through outlier noise elimination, logical multiplication and labeling. In order to verify the method, decellularization of porcine arotic valve was performed by the electrical method. Slice samples were obtained by time and the proposed method was applied.
resultsThe experimental results show that the segmentation of cells and tissues, and quantitative analysis of the number of cells and changes in tissue area during the decellularization process was possible.
conclusionsThe proposed method shows that cell and tissue extraction and quantitative numerical analysis were possible in different brightness of microscopic images.
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