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AKUImg: A database of cartilage images of Alkaptonuria patients

Authors :
Lia Millucci
Silvia Galderisi
Giorgia Giacomini
Vittoria Cicaloni
Monica Bianchini
Annalisa Santucci
Maria Serena Milella
Alberto Rossi
Andrea Bernini
Ottavia Spiga
Publication Year :
2020

Abstract

ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis for patients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. We present an ApreciseKUre plugin, called AKUImg, dedicated to the storage and analysis of AKU histopathological slides, in order to create a Precision Medicine Ecosystem (PME), where images can be shared among registered researchers and clinicians to extend the AKU knowledge network. AKUImg includes a new set of AKU images taken from cartilage tissues acquired by means of a microscopic technique. The repository, in accordance to ethical policies, is publicly available after a registration request, to give to scientists the opportunity to study, investigate and compare such precious resources. AKUImg is also integrated with a preliminary but accurate predictive system able to discriminate the presence/absence of AKU by comparing histopatological affected/control images. The algorithm is based on a standard image processing approach, namely histogram comparison, resulting to be particularly effective in performing image classification, and constitutes a useful guide for non-AKU researchers and clinicians.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....13ac21247a074e3b2a3b53bf7e8062cd