Title :
Automatic cell count in digital images of liver tissue sections
Author :
Mussio, P. ; Pietrogrande, M. ; Bottoni, P. ; Dell´Oca, M. ; Arosio, E. ; Sartirana, E. ; Finanzon, M.R. ; Dioguardi, N.
Author_Institution :
Dept. of Phys., Milan Univ., Italy
Abstract :
A method for identifying and counting cells and biological structures in histological liver tissue sections is presented. The method uses several image processing operators. The final classification results from contextual fusion of different clues. The overall flow of information among the active components of the cell description procedure (CDP) is outlined. The CDP is constructed and validated by a sequence of exploration and confirmation phases. Exploration takes place when a set of known images that is progressively improved until the results are satisfactory is worked out through the CDP. The confirmation phase may then start, working out a new set of images (of the same type but not analyzed before) and proceeding until acceptable sets of agents are generated. The completion of a first exploration phase has identified some major fields of improvement such as the identification of revision criteria for the refinement of the F-nuclei class
Keywords :
computerised pattern recognition; computerised picture processing; liver; medical computing; CDP; F-nuclei class; automatic cell count; biological structure identification; cell description procedure; cell identification; digital images; histological liver tissue sections; image processing; Biological tissues; Biomedical imaging; Cells (biology); Digital images; Eyes; Humans; Image analysis; Image processing; Liver; Physics;
Conference_Titel :
Computer-Based Medical Systems, 1991. Proceedings of the Fourth Annual IEEE Symposium
Conference_Location :
Baltimore, MD
Print_ISBN :
0-8186-2164-8
DOI :
10.1109/CBMS.1991.128958