Title
A 3D Segmentation and Visualization Scheme for Solid and Non-solid Lung Lesions Based on Gaussian Filtering Regularized Level Set
Abstract
The segmentation of Lung lesions is a challenging task because of the complexity of lung lesions surroundings. Lung lesions can be categorized into two types: solid and non-solid. Lots of works have been developed previously to segment one of two types, but only a few are proposed to handle two types at the same time and these methods may be over-segmented or sub-segmented. Therefore, in this study, an effective framework is designed to segment two types of lung lesions in 3-dimension (3D). In the proposed framework, we use a Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) method to produce a 3D rough segmentation which is used as the initial contour of Geodesic Active Contour (GAC) method. SBGFRLS method can deal with the non-solid lung lesions very well because it can use the global information to segment inhomogeneous entities. GAC method can accurately locate the edge using the local information. Finally, we reconstruct and visualize the 3D segmentation results of lung lesions using visualization toolkit (VTK). All of our work is based on the Image Segmentation and Registration Toolkit (ITK) platform. We evaluate our method on the lung lesions CT data sets from 300 patients (280 for solid and 20 for non-solid). Experimental results show that our method can achieve better segmentation and more accurate calculation of 3D volume measurement compared to other two methods, especially in the non-solid type lesions.
Year
DOI
Venue
2014
10.1109/3DV.2014.110
3DV (Workshops)
Keywords
Field
DocType
Geodesic Active Contour, segmentation, lung lesion, level set
Computer vision,Data set,Scale-space segmentation,Pattern recognition,Visualization,Segmentation,Level set,Segmentation-based object categorization,Filter (signal processing),Image segmentation,Artificial intelligence,Mathematics
Conference
Volume
ISSN
Citations 
2
1550-6185
0
PageRank 
References 
Authors
0.34
11
5
Name
Order
Citations
PageRank
Liansheng Wang1155.36
Huangjing Lin2343.20
Xiaoyang Huang311.39
Boliang Wang4264.61
Yiping Chen514820.86