Title :
Hierarchical decision tree for the classification of prostate tissue
Author :
Huynen, A.L. ; Giesen, R.J.B. ; Laduc, R. ; Debruyne, F.M.J. ; Wijkstra, H.
Author_Institution :
BioMedical Engineering, Dept. of Urology, University Hospital Nijmegen PO Box 9101, 6500 HB NIJMEGEN, the Netherlands
fDate :
Oct. 29 1992-Nov. 1 1992
Abstract :
This paper describes an algorithm for the classification of texture in ultrasonographic prostate images. The texture is described by parameters which have to be correlated to the histology of the tissue in the image. An adaptive learn algorithm is used to build a hierarchical decision tree for the partitioning of the parameter space. This tree is then used to predict the probability of malignancy in the tissue.
Conference_Titel :
Engineering in Medicine and Biology Society, 1992 14th Annual International Conference of the IEEE
Conference_Location :
Paris, France
Print_ISBN :
0-7803-0785-2
Electronic_ISBN :
0-7803-0816-6
DOI :
10.1109/IEMBS.1992.5762186
