Carcinogenesis is a multi-step process involving genetic alterations and non-genotoxic mechanisms. The in vitro cell transformation assay allows the monitoring of the neoplastic phenotype by foci formation in suitable cells (e.g. C3H10T1/2 mouse embryo fibroblasts) showing aberrant morphology of massive build-up, polar and multi-layered densely stained cells. The classification of transformed foci in C3H cells relies on light microscopy scoring by a trained human expert based on standard rules. This procedure is time-consuming and prone, in some cases, to subjectivity, thereby leading to possible over- or under-estimation of the carcinogenic potential of tested compounds. Herewith we describe the in vitro neoplastic transformation induced by B[a]P and CdCl 2 , and the development of a foci classifier based on image analysis and statistical classification. The image analysis system, which relies on ‘spectrum enhancement’, is quantitative and extracts descriptors of foci texture and structure. The statistical classification method is based on the Random Forest algorithm. We obtained a classifier trained by using expert’s supervision with a 20% classification error. The proposed method could serve as a basis to automate the in vitro cell transformation assay.
Image analysis and automatic classification of transformed foci / C. URANI; F. M. STEFANINI; L. BUSSINELLI; P. MELCHIORETTO; G. F. CROSTA. - In: JOURNAL OF MICROSCOPY. - ISSN 0022-2720. - STAMPA. - 234:(2009), pp. 269-279. [10.1111/j.1365-2818.2009.03171.x]
Image analysis and automatic classification of transformed foci
STEFANINI, FEDERICO MATTIA;
2009
Abstract
Carcinogenesis is a multi-step process involving genetic alterations and non-genotoxic mechanisms. The in vitro cell transformation assay allows the monitoring of the neoplastic phenotype by foci formation in suitable cells (e.g. C3H10T1/2 mouse embryo fibroblasts) showing aberrant morphology of massive build-up, polar and multi-layered densely stained cells. The classification of transformed foci in C3H cells relies on light microscopy scoring by a trained human expert based on standard rules. This procedure is time-consuming and prone, in some cases, to subjectivity, thereby leading to possible over- or under-estimation of the carcinogenic potential of tested compounds. Herewith we describe the in vitro neoplastic transformation induced by B[a]P and CdCl 2 , and the development of a foci classifier based on image analysis and statistical classification. The image analysis system, which relies on ‘spectrum enhancement’, is quantitative and extracts descriptors of foci texture and structure. The statistical classification method is based on the Random Forest algorithm. We obtained a classifier trained by using expert’s supervision with a 20% classification error. The proposed method could serve as a basis to automate the in vitro cell transformation assay.File | Dimensione | Formato | |
---|---|---|---|
Pagine da urani_JoM_2009_jmi_3171-2-5.pdf
Accesso chiuso
Tipologia:
Versione finale referata (Postprint, Accepted manuscript)
Licenza:
Tutti i diritti riservati
Dimensione
891 kB
Formato
Adobe PDF
|
891 kB | Adobe PDF | Richiedi una copia |
Pagine da urani_JoM_2009_jmi_3171-2-6.pdf
Accesso chiuso
Tipologia:
Versione finale referata (Postprint, Accepted manuscript)
Licenza:
Tutti i diritti riservati
Dimensione
40.91 kB
Formato
Adobe PDF
|
40.91 kB | Adobe PDF | Richiedi una copia |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.