Cytological image segmentation based on iterative generalized Hough transform

Zhuofu Liu; Meimei Liu; Lihua Sui; Li Cheng

doi:10.1117/12.710875

27 October 2006 Cytological image segmentation based on iterative generalized Hough transform

Zhuofu Liu, Meimei Liu, Lihua Sui, Li Cheng

Proceedings Volume 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine; 60473T (2006) https://doi.org/10.1117/12.710875
Event: Fourth International Conference on Photonics and Imaging in Biology and Medicine, 2005, Tianjin, China

Abstract

Automatic exact segmentation of medical images is very important, since applications need to extract precisely the interesting organic features in the human body. An important example is cell detection in cytological and histological images for the diagnosis of breast cancer. In this paper, we propose a time- and memory-efficient algorithm, called Iterative Generalized Hough Transform (IGHT) for automated cytological image segmentation. In addition to lowering memory requirement, the proposed algorithm reduces the excessive time with image scaling. Instead of being applied to a full-sized image, the IGHT scales down to half-sized and quarter-sized images. The proposed algorithm efficiently exploits both region and edge information. The results show that it is a reliable method for segmenting nuclei in cytological images and for extracting components of interest, which is a key step for diagnosing breast cancer and predicting the course of the disease.

Citation Download Citation

Zhuofu Liu, Meimei Liu, Lihua Sui, and Li Cheng "Cytological image segmentation based on iterative generalized Hough transform", Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 60473T (27 October 2006); https://doi.org/10.1117/12.710875

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Hough transforms

Image scaling

Breast cancer

Detection and tracking algorithms

Image processing

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