A texture-based 3D region growing approach for segmentation of ICA through the skull base in CTA

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.

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A Fully Automatic Global Gradient Measure Based 3D Region Growing Solid Tumour Segmentation Method (3D-GGM-RG) for Low Contrast and Low Count Positron Emission Tomography

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2019.2803 ◽

2019 ◽

Vol 9 (9) ◽

pp. 2022-2030

Author(s):

Mahbubunnabi Tamal

Keyword(s):

Positron Emission Tomography ◽

Solid Tumour ◽

Region Growing ◽

Emission Tomography ◽

Segmentation Method ◽

Low Contrast ◽

Tumour Segmentation ◽

Positron Emission ◽

Fully Automatic ◽

3D Region Growing

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

BioMed Research International ◽

10.1155/2015/798303 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 3

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.

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