Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/7309
Title: AKUImg: A database of cartilage images of Alkaptonuria patients
Authors: Rossi, Alberto
Giacomini, Giorgia
Cicaloni, Vittoria 
Galderisi, Silvia 
Milella, Maria Serena 
Bernini, Andrea 
Millucci, Lia 
Spiga, Ottavia 
Bianchini, Monica
Santucci, Annalisa 
Keywords: Alkaptonuria, rare disease, precision medicine, histopatological images
Issue Date: 2020
Project: None 
Journal: COMPUTERS IN BIOLOGY AND MEDICINE
Abstract: 
ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis forpatients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. We present anApreciseKUre 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 registeredresearchers and clinicians to extend the AKU knowledge network. AKUImg includes a new set of AKU imagestaken from cartilage tissues acquired by means of a microscopic technique. The repository, in accordanceto ethical policies, is publicly available after a registration request, to give to scientists the opportunity tostudy, investigate and compare such precious resources. AKUImg is also integrated with a preliminary butaccurate predictive system able to discriminate the presence/absence of AKU by comparing histopatologicalaffected/control images. The algorithm is based on a standard image processing approach, namely histogramcomparison, resulting to be particularly effective in performing image classification, and constitutes a usefulguide for non-AKU researchers and clinicians
Description: 
220964
URI: http://hdl.handle.net/20.500.12779/7309
ISSN: 0010-4825
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