Influence of Active Shape Model Segmentation Method on Optical Reconstruction

Yuqing Hou; Haowen Hu; Fengjun Zhao; Xuelei He; Huangjian Yi; Xiaowei He

doi:10.3788/AOS201838.0211001

[1] Ntziachristos V, Tung C, Bremer C et al. Fluorescence molecular tomography resolves protease activity in vivo[J]. Nature Medicine, 8, 757-760(2002). http://www.nature.com/nm/journal/v8/n7/abs/nm729.html

[2] Milstein A B, Oh S, Webb K J et al. Fluorescence optical diffusion tomography[J]. Applied Optics, 42, 3081-3094(2003).

[3] Schulz R B, Ripoll J, Ntziachristos V. Experimental fluorescence tomography of tissues with noncontact measurements[J]. IEEE Transactions on Medical Imaging, 23, 492-500(2004). http://www.ncbi.nlm.nih.gov/pubmed/15084074

[4] Hou Y Q, Jin M Y, He X W et al. Fluorescence molecular tomography using a stochastic variant of alternating direction method of multipliers[J]. Acta Optica Sinica, 37, 0717001(2017).

[5] Dong F, Hou Y Q, Yu J J et al. Fluorescence molecular tomography via greedy method combined with region-shrinking strategy[J]. Laser & Optoelectronics Progress, 53, 011701(2016).

[6] Zhang X, Yi H J, Hou Y Q et al. Fast reconstruction in fluorescence molecular tomography based on locality preserving projections[J]. Acta Optica Sinica, 36, 0717001(2016).

[7] Li Y, Cho S Y. A method for cell image segmentation using both local and global threshold techniques[C]. Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 183-188(2013).

[8] Zhu D H, Lin S M, Yang Y B. Threshold-based segmentation for 3D medical volumetric images[J]. Computer Science, 40, 269-272(2013).

[9] Mala C, Sridevi M. Multilevel threshold selection for image segmentation using soft computing techniques[J]. Soft Computing, 20, 1793-1810(2015). http://link.springer.com/article/10.1007/s00500-015-1677-6

[10] Shrivakshan G T, Chandrasekar C. A comparison of various edge detection techniques used in image processing[J]. International Journal of Computer Science Issues, 9, 272-276(2012). http://www.oalib.com/paper/2646012

[11] Meenakshisundari P. Kumar S B R. Comparison of various edge detection techniques in tree ring structure[J]. International Journal of Computer Applications, 90, 26-28(2014). http://adsabs.harvard.edu/abs/2014IJCA...90s..26M

[12] Zhu Z W, Liu G R, Liu Q H. Study of first-order edge detection algorithm[J]. Modern Electronics Technique, 32, 88-90(2009).

[13] Liu Y, Jiang T, Zang Y. Region growing method for the analysis of functional MRI data[J]. Neuroimage, 20, 455-465(2003). http://europepmc.org/abstract/MED/14527606

[14] Modi C K, Desai N P. A simple and novel algorithm for automatic selection of ROI for dental radiograph segmentation[C]. 2011 24th Canadian Conference on Electrical and Computer Engineering, 000504-000507(2011).

[15] Verma O P, Hanmandlu M, Susan S et al. A simple single seeded region growing algorithm for color image segmentation using adaptive thresholding[C]. IEEE 2011 International Conference on Communication Systems and Network Technologies, 500-503(2011).

[16] Zhu S, Gao R. A novel generalized gradient vector flow snake model using minimal surface and component-normalized method for medical image segmentation[J]. Biomedical Signal Processing and Control, 26, 1-10(2016). http://www.sciencedirect.com/science/article/pii/S1746809415002025

[17] Sun S, Ren H, Meng F. Abnormal lung regions segmentation method based on improved ASM[C]. IEEE Control and Decision Conference, 5535-5539(2016).

[18] Sharp G C, Sang W L, Wehe D K. ICP registration using invariant features[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 90-102(2002). http://doi.ieeecomputersociety.org/10.1109/34.982886

[19] Yang J, Li H, Campbell D et al. Go-ICP: a globally optimal solution to 3D ICP point-set registration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 2241-2254(2016). http://dl.acm.org/citation.cfm?id=3084750

[20] Zhang L, Choi S I, Park S Y. Robust ICP registration using biunique correspondence[C]. International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, 80-85(2011).

[21] Lee S W, Lee D J, Park H S. A new methodology for gray-scale character segmentation and recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18, 1045-1050(1996). http://dl.acm.org/citation.cfm?id=628382

[22] Cong A X, Wang G. A finite-element-based reconstruction method for 3D fluorescence tomography[J]. Optics Express, 13, 9847-9857(2005). http://www.europepmc.org/abstract/MED/19503194

[23] Cong W, Kumar D, Liu Y et al. A practical method to determine the light source distribution in bioluminescent imaging[C]. SPIE, 5535, 679-686(2004).

[24] Alexandrakis G, Rannou F R, Chatziioannou A F. Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study[J]. Physics in Medicine and Biology, 50, 4225-4241(2005). http://onlinelibrary.wiley.com/resolve/reference/PMED?id=16177541