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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhy Chang-ming Gu Guo-chang Liu Hai-bo Shen Jing Yu Hualong |
| Copyright Year | 2008 |
| Description | Author affiliation: Sch. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin (Zhy Chang-ming; Gu Guo-chang; Liu Hai-bo; Shen Jing; Yu Hualong) |
| Abstract | This image partition plays an important role in both qualitative and quantitative analysis of medical ultrasound images. But medical ultrasound images have features of poor contrast and strong speckle noise and segmenting result may not be satisfactory with traditional image segmentation method. Medical ultrasound images are segmented using image segmentation method based on texture feature and graph cut in this paper. The texture feature parameters are obtained according to gray level co-occurrence matrix. The similarities matrix is made based on texture feature parameters and gray intensity of pixel. We use the spectral graph theoretic framework of Normalized cuts to find partitions of an image based on the similarities matrix. Experimental results show that the method is an effective segmentation method for medical ultrasonic image. |
| Starting Page | 795 |
| Ending Page | 798 |
| File Size | 366635 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769533360 |
| DOI | 10.1109/CSSE.2008.294 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | medical ultrasound images graph cut Image edge detection Speckle texture feature Partitioning algorithms Computer science Image segmentation Ultrasonic imaging Image analysis image segmentation Clustering algorithms gray level co-occurrence matrix Medical diagnostic imaging Biomedical imaging |
| Content Type | Text |
| Resource Type | Article |
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