Article: H&E image analysis pipeline for quantifying morphological features.
Journal of pathology informatics
2023 Volume 14, Page(s) 100339
Abstract: ... pipelines for efficient cell type detection. Herein, we present hematoxylin and eosin (H&E) Image Processing ... pipeline (HEIP) for automatied analysis of scanned H&E-stained slides. HEIP is a flexible and modular open ...
Abstract | Detecting cell types from histopathological images is essential for various digital pathology applications. However, large number of cells in whole-slide images (WSIs) necessitates automated analysis pipelines for efficient cell type detection. Herein, we present hematoxylin and eosin (H&E) Image Processing pipeline (HEIP) for automatied analysis of scanned H&E-stained slides. HEIP is a flexible and modular open-source software that performs preprocessing, instance segmentation, and nuclei feature extraction. To evaluate the performance of HEIP, we applied it to extract cell types from ovarian high-grade serous carcinoma (HGSC) patient WSIs. HEIP showed high precision in instance segmentation, particularly for neoplastic and epithelial cells. We also show that there is a significant correlation between genomic ploidy values and morphological features, such as major axis of the nucleus. |
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Language | English |
Publishing date | 2023-10-05 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 2579241-6 |
ISSN | 2153-3539 ; 2229-5089 |
ISSN (online) | 2153-3539 |
ISSN | 2229-5089 |
DOI | 10.1016/j.jpi.2023.100339 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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