Segmentation method based on transition region extraction for coronary angiograms

2009 ◽  
Author(s):  
Wenwei Kang ◽  
Ke Wang ◽  
Qingzhu Wang ◽  
Donghong An
Keyword(s):  
Transition Region ◽  
Segmentation Method ◽  
Region Extraction ◽  
Coronary Angiograms

The Segmentation Method Based on Fusion Algorithm of Transition Region Extraction for Coronary Angiograms

2012 ◽  
Vol 542-543 ◽  
pp. 616-619 ◽  
Author(s):  
Wen Wei Kang ◽  
Xiao Tao Kang ◽  
Bin Liu
Keyword(s):  
Transition Region ◽  
Coronary Arteries ◽  
Segmentation Method ◽  
Fusion Algorithm ◽  
Small Vessels ◽  
Background Elimination ◽  
Local Complexity ◽  
Region Extraction ◽  
Segmentation Image ◽  
Coronary Angiograms

Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction is proposed. Firstly, the coronary arteries are extracted by using the local complexity method based on Top-hat. Then the coronary arteries are extracted again by using the local complexity method based on Gaussian filter. Finally, the segmentation image is obtained by fusing two extracted coronary arteries images. The experiments indicate that the proposed method has better performance on the small vessels extraction and background elimination. In addition, the method is valuable for diagnosis and the quantitative analysis of vessels.

Automatic Segmentation of Pores in Weld Images Based on Transition Region Extraction

2012 ◽  
Vol 217-219 ◽  
pp. 1964-1967
Author(s):  
Tong Tong ◽  
Yan Cai ◽  
Da Wei Sun ◽  
Peng Liu
Keyword(s):  
Transition Region ◽  
Automatic Segmentation ◽  
Experimental Results ◽  
Gray Level ◽  
Segmentation Method ◽  
Complex Environment ◽  
Weld Defects ◽  
Contrast Enhanced ◽  
Region Extraction ◽  
Low Pass

In allusion to the complex images of weld defects, weak contrast between the target and the background, a new segmentation method based on gray level difference transition region extraction is proposed. The paper analyzes the characteristic of weld defects, and then low-pass filtering and contrast enhanced are used to enhance the clarity. Finally, we extract the transition region and confirm a threshold for defects segmentation. The experimental results show that the method can extract the transition region more accurate, and segment the image much better in complex environment.

scholarly journals CBCT image based segmentation method for tooth pulp cavity region extraction

2019 ◽  
Vol 48 (2) ◽  
pp. 20180236
Author(s):  
Lei Wang ◽  
Ju-peng Li ◽  
Zhi-pu Ge ◽  
Gang Li
Keyword(s):  
Tooth Pulp ◽  
Segmentation Method ◽  
Pulp Cavity ◽  
Cbct Image ◽  
Region Extraction

Underwater Image Transition Region Extraction and Segmentation Based on SVM

2013 ◽  
Vol 397-400 ◽  
pp. 2171-2176 ◽  
Author(s):  
Cong Ping Chen ◽  
Lei Zou ◽  
Wei Wang
Keyword(s):  
Support Vector Machine ◽  
Transition Region ◽  
Extraction Method ◽  
Support Vector ◽  
Gray Level ◽  
Local Difference ◽  
Underwater Image ◽  
Local Complexity ◽  
Region Extraction ◽  
Segmentation Threshold

By analyzing the gray level features of transition region, a new underwater image transition region extraction method based on Support Vector Machine (SVM) is presented. At first, a vector is constructed to fully describe the transition region, which includes local complexity, local difference and neighborhood homogeneity. Then, SVM is applied to train and classify the set of feature vectors, so that the transition region of the underwater image is extracted. Finally, the segmentation threshold is determined by mean of the histogram of the transition region, and the binary result was yielded. The experimental results show that the proposed algorithm can achieve a better transition region extraction and segmentation performance, and automatically select the optimal threshold for transition region extraction.

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