Hyperspectral Placenta Dataset: Hyperspectral Image Acquisition, Annotations, and Processing of Biological Tissues in Microsurgical Training
Date
2023-07-26Author(s)
Puustinen, Sami,Kuopio University Hospital
Hyttinen, Joni,University of Eastern Finland
Elomaa, Antti-Pekka,Kuopio University Hospital
Vrzáková, Hana,University of Eastern Finland
Unique identifier
10.5281/zenodo.8045940Metadata
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Citation
Puustinen, Sami,Kuopio University Hospital. Hyttinen, Joni,University of Eastern Finland. Elomaa, Antti-Pekka,Kuopio University Hospital. Vrzáková, Hana,University of Eastern Finland. , Hyperspectral Placenta Dataset: Hyperspectral Image Acquisition, Annotations, and Processing of Biological Tissues in Microsurgical Training, 2023, 10.5281/zenodo.8045940.Abstract
The dataset consists of 101 hyperspectral images of four fresh human placentas and six hyperspectral images of contrast dyes (i.e., indocyanine green and red and blue food colorant) that were captured in the range 515-900 nm, step = 5 nm. The hyperspectral images were manually annotated, delineating the key anatomical structures: arteries, veins, stroma, and the umbilical cord. Standard reference materials were used for flat-field correction. The dataset can be used to develop machine learning algorithms for the automated classification of biological structures, particularly the classification of superficial and deep vessels and transparent tissue layers.
Keywords
Medical hyperspectral imaging Microsurgical training Tissue classification Hyperspectral dataset Human placenta