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
Rossi, A., Giacomini, G., Cicaloni, V., Galderisi, S., Milella, M.S., Bernini, A., et al. (2020). AKUImg: A database of cartilage images of Alkaptonuria patients. COMPUTERS IN BIOLOGY AND MEDICINE, 122 [10.1016/j.compbiomed.2020.103863].
AKUImg: A database of cartilage images of Alkaptonuria patients
Rossi, A.
;Giacomini, G.;Cicaloni, V.;Galderisi, S.;Milella, M. S.;Bernini, A.;Millucci, L.;Spiga, O.;Bianchini, M.;Santucci, A.
2020-01-01
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 cliniciansFile | Dimensione | Formato | |
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https://hdl.handle.net/11365/1117816