电子、通信与自动控制技术 |
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基于点分布模型的3D模型拟合方法 |
徐铸业1(),赵小强1,2,3,*(),蒋红梅1,2,3 |
1. 兰州理工大学 电气工程与信息工程学院,甘肃 兰州 730050 2. 兰州理工大学 甘肃省工业过程先进控制重点实验室,甘肃 兰州 730050 3. 兰州理工大学 国家级电气与控制工程实验教学中心,甘肃 兰州 730050 |
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3D model fitting method based on point distribution model |
Zhu-ye XU1(),Xiao-qiang ZHAO1,2,3,*(),Hong-mei JIANG1,2,3 |
1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China 2. Key Laboratory of Gansu Advanced Control for Industrial Process, Lanzhou University of Technology, Lanzhou 730050, China 3. National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, Lanzhou 730050, China |
1 |
ALLAN A, KEALLEY C, SQUELCH A, et al Patient-specific 3D printed model of biliary ducts with congenital cyst[J]. Quantitative Imaging in Medicine and Surgery, 2019, 9 (1): 86- 93
doi: 10.21037/qims.2018.12.01
|
2 |
RAVIKUMAR N, GOOYA A, CIMEN S, et al Group-wise similarity registration of point sets using Student’s t-mixture model for statistical shape models[J]. Medical Image Analysis, 2018, 44 (2): 156- 176
|
3 |
CLOUTHIER A L, SMITH C R, VIGNOS M F, et al The effect of articular geometry features identified using statistical shape modelling on knee biomechanics[J]. Medical Engineering and Physics, 2019, 66 (4): 47- 55
|
4 |
MARC A F, STEFFEN S, JOERG N, et al Virtual reconstruction of bilateral midfacial defects by using statistical shape modeling[J]. Journal of Cranio-Maxillofacial Surgery, 2019, 47 (7): 1054- 1059
doi: 10.1016/j.jcms.2019.03.027
|
5 |
HOLLENBECK J F M, CAIN C M, FATTOR J A, et al Statistical shape modeling characterizes three-dimensional shape and alignment variability in the lumbar spine[J]. Journal of Biomechanics, 2018, 69 (3): 146- 155
|
6 |
SHIRK J D, KWAN L, SAIGAL C The use of 3-dimensional, virtual reality models for surgical planning of robotic partial nephrectomy[J]. Urology, 2019, 125 (3): 92- 97
|
7 |
SINDHU V, SOUNDARAPANDIAN S Three-dimensional modelling of femur bone using various scanning systems for modelling of knee implant and virtual aid of surgical planning[J]. Measurement, 2019, 141 (7): 190- 208
|
8 |
徐泽楷. 稀缺样本下基于深度学习的图像超分辨率方法研 究 [D]. 武汉: 华中科技大学, 2019: 11-21. XU Ze-kai. Research on deep learning image super resolution sparse samples [D]. Wuhan: Huazhong University of Science and Technology, 2019: 11-21.
|
9 |
LIU T, QIN S, ZOU D, et al Mesoscopic modeling method of concrete based on statistical analysis of CT images[J]. Construction and Building Materials, 2018, 192 (12): 429- 441
|
10 |
MEAKIN J R, HOPKINS S J, CLARKE A In vivo assessment of thoracic vertebral shape from MRI data using a shape model[J]. Spine Deformity, 2019, 7 (4): 517- 524
doi: 10.1016/j.jspd.2018.10.005
|
11 |
REYNEKE C J F, LÜTHI M, BURDIN V, et al Review of 2-D/3-D reconstruction using statistical shape and intensity models and X-ray image synthesis: toward a unified framework[J]. IEEE Reviews in Biomedical Engineering, 2019, 12: 269- 286
doi: 10.1109/RBME.2018.2876450
|
12 |
NEUBERT A, FRIPP J, ENGSTROM C, et al Statistical shape model reconstruction with sparse anomalous deformations: application to intervertebral disc herniation[J]. Computerized Medical Imaging and Graphics, 2015, 46 (12): 11- 19
|
13 |
DAVIES R H. Learning shape: optimal models for analysing natural variability [D]. Manchester: University of Manchester, 2002: 34-40.
|
14 |
KELEMEN A, SZEKELY G, GERIG G Elastic model-based segmentation of 3-D neuroradiological data sets[J]. IEEE Transactions on medical Imaging, 1999, 18 (10): 828- 839
doi: 10.1109/42.811260
|
15 |
ECK S, WORZ S, MULLEROTT K, et al A spherical harmonics intensity model for 3D segmentation and 3D shape analysis of heterochromatin foci[J]. Medical Image Analysis, 2016, 32 (8): 18- 31
|
16 |
DAVIES R H, COOTES T F, TAYLOR C J. A minimum description length approach to statistical shape modelling [M]// INSANA M F, LEAHY R M. Information processing in medical imaging. [S.l.]: Springer, 2001: 50-63.
|
17 |
PEREZ S I, BERNAL V, GONZALEZ P N Differences between sliding semi-landmark methods in geometric morphometrics, with an application to human craniofacial and dental variation[J]. Journal of Anatomy, 2006, 208 (6): 769- 784
doi: 10.1111/j.1469-7580.2006.00576.x
|
18 |
PLESSERS K, VANDEN B P, VAN D C, et al Virtual reconstruction of glenoid bone defects using a statistical shape model[J]. Journal of Shoulder and Elbow Surgery, 2018, 27 (1): 160- 166
doi: 10.1016/j.jse.2017.07.026
|
19 |
NOLTE D, BULL A M J Femur finite element model instantiation from partial anatomies using statistical shape and appearance models[J]. Medical Engineering and Physics, 2019, 67 (5): 55- 65
|
20 |
HENSELER H, KHAMBAY B, JU X, et al Landmark-based statistical procrustes analysis in the examination of breast shape and symmetry[J]. Handchirurgie, Mikrochirurgie, Plastische Chirurgie, 2014, 46 (6): 342- 349
|
21 |
LUTHI M, GERIG T, JUD C, et al Gaussian process morphable models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40 (8): 1860- 1873
doi: 10.1109/TPAMI.2017.2739743
|
22 |
BEDKOWSKI J, PELKA M, MAJEK K, et al. Open source robotic 3D mapping framework with ROS —robot operating system, PCL—point cloud library and cloud compare [C]// 2015 International Conference on Electrical Engineering and Informatics. Denpasar: IEEE, 2015: 644-649.
|
23 |
YU W, TANNAST M, ZHENG G Non-rigid free-form 2D–3D registration using a B-spline-based statistical deformation model[J]. Pattern Recognition, 2017, 63: 689- 699
doi: 10.1016/j.patcog.2016.09.036
|
24 |
邹涛, 王继成, 黄源, 等 中文文档自动分类系统的设计与实现[J]. 中文信息学报, 1999, 13 (3): 26- 32 ZOU Tao, WANG Ji-cheng, HUANG Yuan, et al The design and implementation of an automatic Chinese documents classification system[J]. Journal of Chinese Information processing, 1999, 13 (3): 26- 32
|
25 |
GUHA S, RASTOGI R, SHIM K Rock: a robust clustering algorithm for categorical attributes[J]. Information Systems, 1999, 25 (5): 345- 366
|
26 |
HAQ R, CATES J, BESACHIO D A, et al. Statistical shape model construction of lumbar vertebrae and intervertebral discs in segmentation for discectomy surgery simulation [M]// VRTOVEC T, YAO J, GLOCKER B, et al. Computational methods and clinical applications for spine imaging. [S.l.]: Springer, 2015: 85-96.
|
27 |
MUTSVANGWA T, BURDIN V, SCHWARTZ C, et al An automated statistical shape model developmental pipeline: application to the human scapula and humerus[J]. IEEE Transactions on Biomedical Engineering, 2014, 62 (4): 1098- 1107
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