A multi-threshold 3D reconstruction algorithm
based on labeled medical images

Abstract

Abstract:

As a traditional surface reconstruction algorithm the marching cubes (MC) is unable to extract multi-

threshold organs at one time. We propose a multi-threshold reconstruction algorithm to divide the target area

and surrounding tissues in the MRI image into several label values. Changing the lables of multi-threshold

organs into brief numbers can decrease the memory space and accelerate the speed of drawing contour surfaces.

We also define the index way of voxel vertexes and isosurface intersecting morphology of multi-threshold

three-dimensional reconstruction, which can avoid the situation of triangle facets and vertexes reuse of the

MC. Furthermore, the contour surface reconstruction of the multi-organ requires only one time scanning of the

MRI image. Experimental results show that the number of facets and vertices is decreased more significantly

when the number of organs is larger and their relationship is closer in comparison with the traditional MC

algorithm, and the reconstruction speed is improved by 30% while the reconstruction effect is guaranteed.

Key words: 3D reconstruction, segmentation, label, marching cubes algorithm

XIAO Hong-xu,YANG Zhi-yong,JIANG Shan,HUANG Zhe,ZHAO Sheng-li.

A multi-threshold 3D reconstruction algorithm

based on labeled medical images

[J]. Computer Engineering & Science.

[1]	XIAO Xin-zheng, HUANG Rui-zhang, CHEN Yan-ping, QIN Yong-bin, SONG Yu-mei, ZHOU Yu-lin, . Corrective-Net: A label association learning module for multi-label text classification [J]. Computer Engineering & Science, 2024, 46(06): 1092-1100.
[2]	FAN Qi, WANG Shan-min, LIU Cheng-guang, LIU Qing-shan. Multi-target domain facial expression recognition based on class-wise feature constraint [J]. Computer Engineering & Science, 2024, 46(05): 836-845.
[3]	LI Xin-jie, WANG Wen-jun, DONG Ling, LAI Hua, YU Zheng-tao, GAO Sheng-xiang, . An unsupervised phoneme segmentation method for Lao language with multi-feature interaction fusion [J]. Computer Engineering & Science, 2024, 46(05): 937-944.
[4]	QIU Xiao-meng, WANG Lin, GU Wen-jun, SONG Wei, TIAN Hao-lai, HU Yu. A time series image semantic segmentation model modified by optical flow [J]. Computer Engineering & Science, 2024, 46(01): 102-110.
[5]	ZHANG Wen-hao, QU Shao-jun. Retinal vessel segmentation based on multi-scale attention feature fusion network with dual-decoder structure [J]. Computer Engineering & Science, 2023, 45(12): 2175-2185.
[6]	YANG Chun-xia, MA Wen-wen, XU Ben, HAN Yu, . A hierarchical graph attention network text classification model that integrates label information [J]. Computer Engineering & Science, 2023, 45(11): 2018-2026.
[7]	HAN Hui-yan, WANG Wen-jun, HAN Xie, KUANG Li-qun, XUE Hong-xin, . A grasp pose estimation method combining semantic instance reconstruction [J]. Computer Engineering & Science, 2023, 45(10): 1822-1829.
[8]	DU Jie, LUO Li-ming, SUN Zhong. Event extraction technology based on ALBERT pre-trained model [J]. Computer Engineering & Science, 2023, 45(04): 711-717.
[9]	MA Dong-mei, HUANG Xin-yue, LI Yu. Image semantic segmentation based on feature fusion and attention mechanism [J]. Computer Engineering & Science, 2023, 45(03): 495-503.
[10]	SHE Xiang-yang, MA Yi-jun. An improved semantic segmentation algorithm for remote sensing images [J]. Computer Engineering & Science, 2023, 45(03): 504-511.
[11]	YANG Chun-xia, YAO Si-cheng, SONG Jin-jian, . A Chinese sentiment analysis model combining character and word information [J]. Computer Engineering & Science, 2023, 45(03): 512-519.
[12]	LI Zhong-rui, CUI Bin-ge, YANG Guang, ZHANG Hao-qing. A coastline edge detection network based on deep learning [J]. Computer Engineering & Science, 2022, 44(12): 2220-2229.
[13]	CAI Yu-qi, GUO Wei-bin. A multi-level semantic information fusion coding method for sequence labeling [J]. Computer Engineering & Science, 2022, 44(12): 2266-2272.
[14]	WU Cong-zhong, DONG Hao, FANG Jing. An adaptive filtering remote sensing image segmentation network based on attention mechanism [J]. Computer Engineering & Science, 2022, 44(11): 2010-2018.
[15]	JIANG Yun, LIU Wen-huan, LIANG Jing. Retinal vessel segmentation network with joint attention and Transformer [J]. Computer Engineering & Science, 2022, 44(11): 2037-2047.

A multi-threshold 3D reconstruction algorithm

based on labeled medical images

PDF

Knowledge

Abstract

Cite this article

share this article

Related Articles 15

Recommended Articles

Metrics

Comments