Comparative assessment of 3D region growing methods for lung airway segmentation : evaluation with pathological and normal cases

2007 ◽  
pp. 2525-2527
Author(s):  
Sang Joon Park ◽  
Jong Hyo Kim ◽  
Sang Ho Lee ◽  
Kwang Gi Kim
Keyword(s):  
Region Growing ◽  
Comparative Assessment ◽  
Segmentation Evaluation ◽  
Airway Segmentation ◽  
3D Region Growing

scholarly journals Automated Localized Approach for Airway Segmentation in 3D Chest CT Volume

2020 ◽  
Vol 13 (4) ◽  
pp. 1671-1682
Author(s):  
Anita Khanna ◽  
Narendra Digambar Londhe ◽  
Shubhrata Gupta
Keyword(s):  
Lung Diseases ◽  
Region Growing ◽  
Volume Effect ◽  
Bronchial Tree ◽  
Test Cases ◽  
Detection Techniques ◽  
Airway Segmentation ◽  
Unsupervised Approach ◽  
3D Region Growing ◽  
Ct Volume

Bronchial airway structure and morphology identification is very useful for analysis of many lung diseases. Since, the human tracheo-bronchial tree is a dyadic non-symmetric branching network which is very complex and its manual tracing is quite tedious and unwieldy. Moreover, automatic detection techniques for airway are quite challenging. This is due to its complexity and fading off the airway intensity because of the smaller asynchronous branching and noise in the image reconstruction. In this paper, an unsupervised approach for segmentation of localized airway has been proposed after segmenting the lung region. Firstly, airways are segmented out by using 3D region growing techniques with intensity constrained to prevent leakages. This results in limited segmentation of airways due to partial volume effect and leakage risk. Further, deeper bronchial branches are segmented by applying adaptive morphological techniques on 3D segmented lungs. Then, these two results are combined followed by 3D region growing to get complete segmentation of airway. The proposed technique is tested on Exact’09 20 test cases and evaluated by Exact’09 team. The performance of the proposed approach is quite reliable in segmenting distal branches with reasonable leakages. The advantage of this scheme is that it is easy to implement, fully automated, and time efficient.

Shape Prior Integrated in an Automated 3D Region Growing Method

2007 ◽  
Author(s):  
J-L. Rose ◽  
Ch. Revol-Muller ◽  
Mo. Almajdub ◽  
Em. Chereul ◽  
Ch. Odet
Keyword(s):  
Region Growing ◽  
Shape Prior ◽  
3D Region Growing

scholarly journals Automatic liver vessel segmentation using 3D region growing and hybrid active contour model

2018 ◽  
Vol 97 ◽  
pp. 63-73 ◽  
Author(s):  
Ye-zhan Zeng ◽  
Sheng-hui Liao ◽  
Ping Tang ◽  
Yu-qian Zhao ◽  
Miao Liao ◽  
...  
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Region Growing ◽  
Vessel Segmentation ◽  
Contour Model ◽  
3D Region Growing

scholarly journals Computed Tomography Colonography Technique: The Role of Intracolonic Gas Volume

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Patrick D. McLaughlin ◽  
Kevin P. Murphy ◽  
Lee Crush ◽  
Owen J. O'Connor ◽  
Joseph P. Coyle ◽  
...  
Keyword(s):  
Image Acquisition ◽  
Region Growing ◽  
Volumetric Analysis ◽  
Point Scale ◽  
Single Institution ◽  
Bowel Segments ◽  
Gas Volume ◽  
The Relationship ◽  
3D Region Growing

Introduction. Poor distention decreases the sensitivity and specificity of CTC. The total volume of gas administered will vary according to many factors. We aim to determine the relationship between the volume of retained gas at the time of image acquisition and colonic distention and specifically the presence of collapsed bowel segments at CTC.Materials and Methods. All patients who underwent CTC over a 12-month period at a single institution were included in the study. Colonic luminal distention was objectively scored by 2 radiologists using an established 4-point scale. Quantitative analysis of the volume of retained gas at the time of image acquisition was conducted using the threshold 3D region growing function of OsiriX.Results. 108 patients were included for volumetric analysis. Mean retained gas volume was 3.3 L. 35% (38/108) of patients had at least one collapsed colonic segment. Significantly lower gas volumes were observed in the patients with collapsed colonic segments when compared with those with fully distended colons 2.6 L versus 3.5 L (P=0.031). Retained volumes were significantly higher for the 78% of patients with ileocecal reflux at 3.4 L versus 2.6 L without ileocecal reflux (P=0.014).Conclusion. Estimation of intraluminal gas volume at CTC is feasible using image segmentation and thresholding tools. An average of 3.5 L of retained gas was found in diagnostically adequate CTC studies with significantly lower mean gas volume observed in patients with collapsed colonic segments.

scholarly journals Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Shuo-Tsung Chen ◽  
Tzung-Dau Wang ◽  
Wen-Jeng Lee ◽  
Tsai-Wei Huang ◽  
Pei-Kai Hung ◽  
...  
Keyword(s):  
Coronary Arteries ◽  
Medical Image ◽  
Region Growing ◽  
Ground Truth ◽  
Discrete Wavelet ◽  
Segmentation Method ◽  
3D Dwt ◽  
Initial Segmentation ◽  
3D Discrete Wavelet Transform ◽  
3D Region Growing

Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies.Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries.Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed.Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

3D region growing integrating adaptive shape prior

2008 ◽  
Author(s):  
Jean-Loic Rose ◽  
Chantal Revol-Muller ◽  
Jean-Baptiste Langlois ◽  
Marc Janier ◽  
Christophe Odet
Keyword(s):  
Region Growing ◽  
Shape Prior ◽  
3D Region Growing
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