NDLI: Automatic Segmentation of Rat Mammary Glands from Serial MRI Images

Content Provider	IEEE Xplore Digital Library
Author	Shengxian Tu Su Zhang Wei Yang Xuesong Lu Yazhu Chen
Copyright Year	2007
Description	Author affiliation: Shanghai Jiao Tong Univ., Shanghai (Shengxian Tu; Su Zhang; Wei Yang; Xuesong Lu; Yazhu Chen)
Abstract	A novel framework for automatic segmentation of rat mammary glands in MRI image sequences is presented in this paper. The Cartoon-Texture model is utilized in serial image segmentation to decompose the image into cartoon image and texture image. Then two-phase direct energy segmentation based on Chan-Vese active contour model is implemented on the cartoon image to partition the image into a set of regions. Seeds searching technology is applied iteratively on the texture image to find valid seeds for extracting the whole gland boundary points from the generated regions by a tracing algorithm we proposed. In iteration every time, texture images and features of the image patch around the seed are updated for new seeds searching and segmentation. Our segmentation approach does not require that the number of glands be identical or the location of the glands be close among consecutive images. Experiments show that our method is effective and efficient.
Starting Page	694
Ending Page	698
File Size	1468685
Page Count	5
File Format	PDF
ISBN	9781424410774
DOI	10.1109/ICCME.2007.4381827
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Magnetic resonance imaging Mammary glands Iterative algorithms Breast cancer Image sequences Partitioning algorithms Medical diagnostic imaging Active contours Biomedical imaging
Content Type	Text
Resource Type	Article

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