Paper # 042 | Versión en Español |
Marco Masseroli, Ph.D., Francisco O'Valle, Miguel Andújar, César Ramírez, Mercedes Gómez-Morales, Raimundo G. Del Moral.
Department of Pathology, School of Medicine and University Hospital, University of Granada, 18012 Granada, Spain
Dpto. de Anatomía Patológica, Facultad de Medicina, Avda. de Madrid 11 - 18012 Granada, SPAIN
[Introduction] [Materials & Methods] [Results] [Pictures] [Discussion] [Bibliography] [Comments]
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RESULTS AND DISCUSSION: The image processing algorithms described here automatically segment interstitial fibrosis and mesangial matrix with Kurita's automatic thresholding and morphological filtering. The glomerular region is extracted by a simple interactive step and an automatic mathematical morphology algorithm, while the glomerular tuft is automatically segmented with automatic thresholding and a sequence of Boolean and mathematical morphology operations. All extracted areas are automatically quantified in absolute (µm²) and relative (%) values. For validation, interstitial fibrosis, mesangial matrix, glomerular and glomerular tuft areas were manually segmented and their quantifications statistically compared with those obtained automatically. Statistical analyses showed significant intra- and interoperator variability in manual segmentation of interstitial fibrosis, mesangial matrix and glomerular tuft areas. Automatic quantifications of the same areas did not differ significantly from their mean manual evaluations. Interactive identification of the glomerular region shoed no significant intra- or interoperator variability.
CONCLUSION: The image analysis application reported here is an easy-to-use instrument for rapidly quantifying interstitial fibrosis and glomerular morphology in the same renal tissue section. Validation tests showed that Fibrosis HR produces objective, fully reproducible, precise and reliable quantifications. It therefore facilitates the evaluation of interstitial and renal pathologies and improves the accuracy of clinicopathological evaluations of renal diseases in human biopsies.
Marco
Masseroli is a postdoctoral
fellow of the Pathology Departament of the School of
Medicine of the University of Granada, where he develops
image analysis applications in histopathological
videomicroscopy. Granada, besides being world wide known for the Alhambra monument, is the most important university town of the Andalucía region. Located in the south of Spain enjoys the vicinity both of "Costa del Sol" and "Sierra Nevada". |
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