Automatic heart wall contour extraction from MR images using active contour models: Initial contour setting based on principal component analysis

2003 ◽  
Vol 34 (4) ◽  
pp. 72-82 ◽  
Author(s):  
Mayumi Yuasa ◽  
Mutsumi Watanabe ◽  
Masahide Nishiura ◽  
Kojiro Yamaguchi ◽  
Takeshi Kondo ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Active Contour ◽  
Principal Component ◽  
Component Analysis ◽  
Initial Contour ◽  
Contour Extraction ◽  
Mr Images ◽  
Active Contour Models ◽  
Contour Models ◽  
Heart Wall

scholarly journals Principal Component Analysis of Dynamic Relative Displacement Fields Estimated from MR Images

PLoS ONE ◽  
2011 ◽  
Vol 6 (7) ◽  
pp. e22063 ◽  
Author(s):  
Teresa M. Abney ◽  
Yuan Feng ◽  
Robert Pless ◽  
Ruth J. Okamoto ◽  
Guy M. Genin ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Relative Displacement ◽  
Mr Images ◽  
Displacement Fields

Heuristic Initialization for Active Contour Models in CT/MRI Image Processing

2015 ◽  
Vol 15 (03) ◽  
pp. 1550010
Author(s):  
Hao Liu ◽  
Hongbo Qian ◽  
Ning Dai ◽  
Jianning Zhao
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Heuristic Method ◽  
Initial Contour ◽  
Active Contour Models ◽  
Contour Model ◽  
Segmentation Approach ◽  
Edge Points ◽  
Contour Models ◽  
Level Set Evolution

It is an important segmentation approach of CT/MRI images to automatically extract contours in every slice using active contour models. The key point of the segmentation approach is to automatically construct initial contours for active contour models because any active contour model is sensitive to its initial contour. This paper presents an algorithm to construct such initial contours using a heuristic method. Assume that the contour in previous slice (previous contour) is accurate. The contour in the current slice (current contour) is constructed according to the previous contour using the way: Recognition and link of edge points of tissues according to the previous contour. The contour linking edge points is used as the initial contour of the distance regularized level set evolution (DRLSE) method and then an accurate contour can be extracted in the current slice.

Intracranial contour extraction with active contour models

1997 ◽  
Vol 7 (2) ◽  
pp. 353-360 ◽  
Author(s):  
Sumiaki Matsumoto ◽  
Reinin Asato ◽  
Tomohisa Okada ◽  
Junji Konishi
Keyword(s):  
Active Contour ◽  
Contour Extraction ◽  
Active Contour Models ◽  
Contour Models

Automatic MRI Brain Tumor Segmentation System Based on Localizing Active Contour Models

2011 ◽  
Vol 219-220 ◽  
pp. 1342-1346 ◽  
Author(s):  
Ying Wang ◽  
Zhi Xian Lin ◽  
Jian Guo Cao ◽  
Mao Qing Li
Keyword(s):  
Brain Tumor ◽  
Active Contour ◽  
Automatic Segmentation ◽  
Brain Mri ◽  
Initial Contour ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
Active Contour Models ◽  
Mri Brain ◽  
Contour Models

In this paper, an automatic segmentation system was developed for MRI brain tumor. Local region-based active contour models were suitable for heterogeneous features of brain MRI image. But the models are sensitive to initial contour, which generally requires manual setting. An automatic MRI brain tumor segmentation system were developed based on localized contour models, which can identify tumor-dominant slice, set initial contour automatically and segment tumor’s contours from all MRI slices autonomously. K-means clustering and grayscale analysis were combined to identify tumor-dominant slice. Multi-threshold algorithm with the aid of erosion and dilation operators was adopted to obtain an initial contour for the tumor-dominant slice. The segmentation contour from the local active contour models was applied as initial contours of two-side neighboring slices. MRI brain tumor data were applied to validate the automatic segmentation system.

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