Shape classification of malignant lymphomas and leukemia by morphological watersheds and ARMA modeling

Mehmet Celenk; Yinglei Song; Limin Ma; Min Zhou

doi:10.1117/12.481379

15 May 2003 Shape classification of malignant lymphomas and leukemia by morphological watersheds and ARMA modeling

Mehmet Celenk, Yinglei Song, Limin Ma, Min Zhou

Author Affiliations +

Proceedings Volume 5032, Medical Imaging 2003: Image Processing; (2003) https://doi.org/10.1117/12.481379
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

A new algorithm that can be used to automatically recognize and classify malignant lymphomas and lukemia is proposed in this paper. The algorithm utilizes the morphological watershed to extract boundaries of cells from their grey-level images. It generates a sequence of Euclidean distances by selecting pixels in clockwise direction on the boundary of the cell and calculating the Euclidean distances of the selected pixels from the centroid of the cell. A feature vector associated with each cell is then obtained by applying the auto-regressive moving-average (ARMA) model to the generated sequence of Euclidean distances. The clustering measure J3=trace{inverse(Sw^-1)Sm} involving the within (Sw) and mixed (Sm) class-scattering matrices is computed for both cell classes to provide an insight into the extent to which different cell classes in the training data are separated. Our test results suggest that the algorithm is highly accurate for the development of an interactive, computer-assisted diagnosis (CAD) tool.

Citation Download Citation

Mehmet Celenk, Yinglei Song, Limin Ma, and Min Zhou "Shape classification of malignant lymphomas and leukemia by morphological watersheds and ARMA modeling", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.481379

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