Application of Improved Voxels Growth Algorithm in Cardiac Local Vascular Extraction

Guoyin Ren; Xiaoqi Lü; Nan Yang; Dahua Yu; Xiaofeng Zhang; Tao Zhou

doi:10.3788/LOP55.061701

Laser & Optoelectronics Progress, Volume. 55, Issue 6, 061701(2018)

Application of Improved Voxels Growth Algorithm in Cardiac Local Vascular Extraction

Guoyin Ren¹, Xiaoqi Lü¹, Nan Yang^2、*, Dahua Yu¹, Xiaofeng Zhang¹, and Tao Zhou¹

¹School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 0 14010, China

²Baotou Medical College, Baotou, Inner Mongolia 0 14010, China

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Figures & Tables(8)

Fig. 1. Flow chart of finding the edge of the voxel according to similarity table

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Fig. 2. Topology constraint diagram of voxels in blood vessels

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Fig. 3. (a) Three-dimensional reconstruction of thoracic cavity and (b) extracted local blood vessel cluster

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Fig. 4. Extraction of local blood vessels from cardiac local AABB bounding box

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Fig. 5. Segmentation results before and after the algorithm improving. (a) Before improving; (b) after improving

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Table 1. Comparative evaluation for similarity measure

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Table 1. Comparative evaluation for similarity measure

Similaritymeasure	Operating	R_a	R_b	R_c	R_d	R_e	Adjacent voxelnumbers	Similar voxelnumbers
Meansquareerror	Beforeregistration	1189.25	1147.69	1123.43	1114.16	1101.87	26	8
Meansquareerror	Afterregistration	3487.81	3479.15	3427.48	3404.97	33871.36	26	17
Correlationcoefficient	Beforeregistration	0.97152	0.97102	0.96785	0.96548	0.96229	26	12
Correlationcoefficient	Afterregistration	0.99241	0.99216	0.99178	0.99004	0.98459	26	18
Mattersinformation	Beforeregistration	-1.02594	-1.02234	-1.02119	-1.02101	-1.02078	26	11
Mattersinformation	Afterregistration	-1.37748	-1.37536	-1.37493	-1.37299	-1.37179	26	15

Table 2. Segmentation accuracy evaluation

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Table 2. Segmentation accuracy evaluation

Figurenumber	Traditional voxels growth algorithm				Improved voxels growth algorithm
Figurenumber	Sensitivity	Specificity	Accuracy	Kappa	Sensitivity	Specificity	Accuracy	Kappa
1	0.5974	0.7477	0.8785	0.7664	0.8112	0.9012	0.9214	0.8785
2	0.6348	0.6336	0.8826	0.8204	0.8105	0.9016	0.9114	0.8568
3	0.6852	0.8125	0.8789	0.7344	0.7929	0.9148	0.9322	0.8897
4	0.5374	0.7756	0.8664	0.8010	0.8188	0.9248	0.9483	0.8924
5	0.7259	0.7978	0.8997	0.8452	0.8354	0.9321	0.9324	0.8899
Averagevalue	0.6348	0.8489	0.8347	0.8327	0.8137	0.9124	0.9247	0.8814

Table 3. Voxel growth evaluation before and after algorithm improving

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Table 3. Voxel growth evaluation before and after algorithm improving

Algorithms andattributes	Size of boundingbox (x, y, z)	Number of voxelsin volume	Number ofvoxels on surface	Voxels growth timeinside model /s	Voxels growthtime of surface /s
Automatic voxelsgrowth algorithm	(28, 40, 23)	26625	2957	103.89	5.83
Semi-automatic voxelsgrowth algorithm	(3, 5.3, 2)	3152	345	5.59	1.46
Improved voxelsgrowth algorithm	(3, 5.3, 2)	3152	345	3.78	1.12

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Guoyin Ren, Xiaoqi Lü, Nan Yang, Dahua Yu, Xiaofeng Zhang, Tao Zhou. Application of Improved Voxels Growth Algorithm in Cardiac Local Vascular Extraction[J]. Laser & Optoelectronics Progress, 2018, 55(6): 061701

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Paper Information

Category: Medical Optics and Biotechnology

Received: Oct. 8, 2017

Accepted: --

Published Online: Apr. 10, 2019

The Author Email: Nan Yang (812216021@qq.com)

DOI:10.3788/LOP55.061701

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology