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http://hdl.handle.net/10553/132037
Title: | Histological Hyperspectral Glioblastoma Dataset (HistologyHSI-GB) | Authors: | Ortega, Samuel Quintana Quintana, Laura León, Raquel Fabelo, Himar Plaza, María de la Luz Camacho, Rafael Callicó, Gustavo M. |
UNESCO Clasification: | 3314 Tecnología médica | Keywords: | Computational Pathology Classification |
Issue Date: | 2024 | Journal: | Scientific data | Abstract: | Hyperspectral (HS) imaging (HSI) technology combines the main features of two existing technologies: imaging and spectroscopy. This allows to analyse simultaneously the morphological and chemical attributes of the objects captured by a HS camera. In recent years, the use of HSI provides valuable insights into the interaction between light and biological tissues, and makes it possible to detect patterns, cells, or biomarkers, thus, being able to identify diseases. This work presents the HistologyHSI-GB dataset, which contains 469 HS images from 13 patients diagnosed with brain tumours, specifically glioblastoma. The slides were stained with haematoxylin and eosin (H&E) and captured using a microscope at 20× power magnification. Skilled histopathologists diagnosed the slides and provided image-level annotations. The dataset was acquired using custom HSI instrumentation, consisting of a microscope equipped with an HS camera covering the spectral range from 400 to 1000 nm. | URI: | http://hdl.handle.net/10553/132037 | DOI: | 10.1038/s41597-024-03510-x | Source: | Scientific Data[EISSN 2052-4463],v. 11 (1), (Diciembre 2024) |
Appears in Collections: | Artículos |
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