Segmentation of heart by using Gabor filter and Principal component Analysis
Segmentation of the heart across a cardiac cycle is a problem of interest because the left ventricles proper function,pumping oxygenated blood to the entire body,is vital for normal human activity.Having segmentations of the heart over time allows cardiologists to assess the dynamic behavior of the human heart (using,e.g.,the ejection fraction).Segmented heart boundaries can also be useful for further quantitative analysis. Texture features has been widely used in object recognition,image analysis and many others.Gabor filter has emerged as one of the most popular ones.Gabor filter based feature extractor is a Gabor filter defined by its parameters including frequencies,orientations and smooth parameters of Gaussian envelope. Snakes have been used extensively in locating object boundaries.However,in the medical imaging field,many organs in close proximity have similar intensity values,limiting the usefulness of snakes in segmentation of abdominal organs.The gradient vector flow snake is used to test the benefits of running snakes on texture features from orientation based Gabor Filter.A proposed algorithm is GVF (gradient vector Flow) with ASM (Active Shape Model) to overcome several drawbacks in the original framework.The algorithm is completely automatic and computationally efficient
Gabor filter principal component analysis(PCA) Gradient Vector Flow (GVF)
Shreyasi Watve R.Sreemathy
PICT,Pun PTCT,Pune
国际会议
2011 International Conference on Computer and Network Engineering(ICCNE 2011)(2011年计算机与网络工程国际会议)
郑州
英文
442-446
2011-06-17（万方平台首次上网日期，不代表论文的发表时间）