Unstained and H&E stained whole slide image pairs of anterior prostate tissue

Beskrivning

The data set consists of 81 registered whole slide image pairs, a pair represents unstained and H&E stained images of the same tissue sample. In addition to that, it also contains a tissue mask for each whole slide image pair. The samples are used for studying the histological feasibility of AI-driven virtual histopathology staining. Imaging was performed using Thunder Imager 3D Tissue slide scanner (Leica Microsystems, Wetzlar, Germany) equipped with DMC2900 camera and HC PL APO 40x/0.95 DRY objective with an isotropic pixel resolution of 0.353 µm.
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Publiceringsår

2022

Typ av data

Upphovspersoner

Advancing Breast Cancer histopathology towards AI-based Personalised medicine (ABCAP) - Utgivare

Biolääketieteen laitos

Pekka Ruusuvuori - Upphovsperson

Umair Khan - Upphovsperson

Lääketieteen laitos, biolääketieteen yksikkö

Leena Latonen Orcid -palvelun logo - Upphovsperson

Sonja Koivukoski - Upphovsperson

Projekt

Övriga uppgifter

Vetenskapsområden

Data- och informationsvetenskap; Biomedicinska vetenskaper

Språk

engelska

Öppen tillgång

Öppet

Licens

Creative Commons Attribution 4.0 International (CC BY 4.0)

Nyckelord

deep learning, artificial intelligence, whole slide images, Microscopy, hematoxylin & eosin (HE), histology, light microscopy, virtual staining, AI, GAN

Ämnesord

Temporal täckning

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