Title :
Automatic region growing method using GSmap and spatial information on ultrasound images
Author :
Oghli, Mostafa Ghelich ; Fallahi, Alireza ; Pooyan, Mohammad
Author_Institution :
Biomed. Eng. Dept., Shahed Univ., Tehran, Iran
Abstract :
Ultrasound image segmentation is a critical issue in medical image analysis and visualization. Identifying the boundaries of abnormal regions in some cases is challenging task. In this paper, we propose a full automatic region growing algorithm. The seed point has been automatically selected based on textural features from co-occurrence matrix and run length method. Thresholding simplicity and the spatial information of pixels used for segmentation of these images. This is best method for segmentation of ultrasound images because it is not affected by speckle noise and also preserves spatial information. In addition this method can reduce the time for manual post-processing due to over-segmentation result from ordinary region growing with intensity criteria. We have tested this method in segmenting some objects from ultrasound images and obtained good results.
Keywords :
biomedical ultrasonics; image resolution; image segmentation; image texture; medical image processing; speckle; GSmap; automatic region growing method; co-occurrence matrix; gray space map; medical image analysis; medical image visualization; pixels; run length method; spatial information; speckle noise; textural features; thresholding; ultrasound image segmentation; Active contours; Biomedical engineering; Biomedical imaging; Frequency; Image segmentation; Image texture analysis; Pixel; Speckle; Ultrasonic imaging; Visualization; Gray space map; Otsu method; Region growing; Texture features; Ultrasound image; component;
Conference_Titel :
Electrical Engineering (ICEE), 2010 18th Iranian Conference on
Conference_Location :
Isfahan
Print_ISBN :
978-1-4244-6760-0
DOI :
10.1109/IRANIANCEE.2010.5507108