An automatic fusion algorithm for multi-modal medical images

References

• Aktar MN, Alam MJ, Pickering M, Webb A, Perriman D. 2015. Non-Rigid Registration of Cervical Spine MRI Volumes. 37th Annual International conference of the IEEE Engineering in Medicine and Biology Society, EMBC. 2015:1997–2000.
   Google Scholar
• Ali F, El-Dokany I, Saad A, El-Samie FA. 2008. Fusion of MR and CT images using the curvelet transform. IEEE Radio Science Conference (NRSC). 1–8.
   Google Scholar
• Anbumozhi S, Manoharan P. 2014. Performance analysis of medical image fusion using multimodal graph cut algorithm. Int J Adv Res Comput Eng Technol. 3:802–807.
   Google Scholar
• Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, Evans AC. 1998. IEEE Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging. 17:463–468.
   PubMed Web of Science ®Google Scholar
• Cvejic N, Loza A, Bull D, Canagarajah N. 2005. A similarity metric for assessment of image fusion algorithms. Int J Sign Process. 2:178–182.
   Google Scholar
• Daneshvar S, Ghassemian H. 2010. MRI and PET image fusion by combining IHS and retina-inspired models. J Inf Fusion. 11:114–123. Elsevier.
   Web of Science ®Google Scholar
• Du J, Li W, LU F, Xiao B 2016. An overview of multi-modal medical image fusion. Neurocomputing. 215: 3–20. Elsevier
   Web of Science ®Google Scholar
• Hahn M. Samadzadegan F. 2004. A study of image fusion techniques in remote sensing. Proceedings on the 20th ISPRS Congress Geoimagery Bridging Continents; p. 889–895.
   Google Scholar
• Harika A. 2014a. Image fusion based on DTCWT & PCA in presence of noise. Int J Adv Res Comput Commun Eng. 3:8492–8495.
   Google Scholar
• Harika A. 2014b. Image fusion based on DTCWT and PCA. Int J Eng Res Technol. 3:1206–1209.
   Google Scholar
• He C, Liu Q, Li H, Wang H. 2010. Multimodal medical image fusion based on IHS and PCA. Symp Secur Detection Inf Process. Elsevier. 7:280–285.
   Google Scholar
• James BV AP, Dasarathy BV. 2017. Medical image fusion: A survey of the state of the art. Inf Fusion. 19: 4–19. Elsevier
   Google Scholar
• Javed U, Riaz MM, Ghafoor A, Ali SS, Cheema TA. 2014. MRI and PET image fusion using fuzzy logic and image local features. Sci World J. Hindawi Publishing Corporation. 2014:1–8.
   Google Scholar
• Jiang Y, Wang M. 2014. Elsevier; Image fusion with morphological component analysis. J Inf Fusion. 18:107–118.
   Web of Science ®Google Scholar
• Kancharla S, Madhu T. 2015. Development of image fusion methods and evaluation of quality parameters. e-J. Sci Technol. 10:91–99.
   Google Scholar
• Kekre H. 2013. Review on image fusion techniques and performance evaluation parameters. Int J Eng Sci Technol. 5:880–889.
   Google Scholar
• Krishnamoorthy S, Soman K. 2010. Implementation and comparative study of image fusion algorithms. Int J Comput Appl. 9:25–35.
   Google Scholar
• Li S, Kang X, Fang L, HuJ, Yin H. 2017. Pixel-level image fusion: A survey of the state of the art. Inf Fusion. 33: 100–112. Elsevier
   Web of Science ®Google Scholar
• Liu Z, Yin H, Chai Y, Yang SX. 2014. Elsevier; A novel approach for multimodal medical image fusion. Expert Syst Appl. 41:7425–7435.
   Web of Science ®Google Scholar
• Li S, Yang B, Hu J. 2011. Elsevier; Performance comparison of different multi-resolution transforms for image fusion. J Inf Fusion. 12:74–84.
   Web of Science ®Google Scholar
• Mercier L, Del Maestro RF, Petrecca K, Araujo D, Haegelen C, Collins DL. 2012. American Association of Physicists in Medicine; Online database of clinical MR and ultrasound images of brain tumors. Med Phys. 39:3253–3261.
   PubMedGoogle Scholar
• Naidu V. 2014. Springer; Hybrid DDCT-PCA based multi sensor image fusion. J Opt. 43:48–61.
   Google Scholar
• Naidu V, Raol J. 2008. Pixel-level image fusion using wavelets and principal component analysis. Defence Sci J. 58:338–352.
   Web of Science ®Google Scholar
• Pajares G, Manuel de laCruz J. 2004. A wavelet-based image fusion tutorial. J Pattern Recognit. 37:1855–1872. Elsevier.
   Web of Science ®Google Scholar
• Piella G, Heijmans H. 2003. A new quality metric for image fusion. Proceedings of IEEE International Conference on Image Processing (ICIP). 173–176.
   Google Scholar
• Qing X, Shuai X, Bing T, Jiansheng L, Zexun G. 2004. Complex Wavelets and its application to image fusion. 20th ISPRS Congress Technical Commission III. Vol. 35, p. 1–6.
   Google Scholar
• Rani K, Sharma R. 2013. Study of different image fusion algorithm. Int J Emerg Technol Adv Eng. 3:288–291.
   Google Scholar
• Rivaz H, Chen SJS, Collins DL. 2015. IEEE; Automatic deformable MR-Ultrasound registration for image-guided neurosurgery. IEEE Trans Med Imaging. 34:366–380.
   PubMed Web of Science ®Google Scholar
• Sadjadi F. 2005. Comparative image fusion analysais. IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops. 1–8.
   Google Scholar
• Sahu DK, Parsai M. 2012. Different image fusion techniques-a critical review. Int J Mod Eng Res. 2:4298–4301.
   Google Scholar
• Sawant S, Mane S. 2014. Image fusion of CT/MRI using DWT, PCA methods and analog DSP processor. Int J Eng Res Appl. 2248–9622.
   Google Scholar
• Selesnick IW, Baraniuk RG, Kingsbury NC. 2005. IEEE; The dual-tree complex wavelet transform. IEEE Sig Process Mag. 22:123–151.
   Web of Science ®Google Scholar
• Shlens J. 2014. A tutorial on principal component analysis. arXiv preprint arXiv:1404.1100.
   Google Scholar
• Singh R, Khare A. 2014. Fusion of multimodal medical images using Daubechies complex wavelet transform--A multiresolution approach. Inf Fusion. 19: 49–60. Elsevier
   Web of Science ®Google Scholar
• Sui J, Adali T, Yu Q, Chen J, Calhoun VD. 2012. Elsevier; A review of multivariate methods for multimodal fusion of brain imaging data. J Neurosc Methods. 204:68–81.
   PubMed Web of Science ®Google Scholar
• Tu TM, Su SC, Shyu HC, Huang PS. 2001. Elsevier; A new look at IHS-like image fusion methods. Inf Fusion. 2:177–186.
   Google Scholar
• Wang Z, Bovik AC. 2002. IEEE; A universal image quality index. Sign Process Lett. IEEE. 9:81–84.
   Web of Science ®Google Scholar
• West J, Fitzpatrick JM, Wang MY, Dawant BM, Maurer CR Jr, Kessler RM, Maciunas RJ, Barillot C, Lemoine D, Collignon A, et al. 1997. Comparison and evaluation of retrospective intermodality brain image registration techniques. J Comput Assisted Tomography. 21:554–568.
   PubMed Web of Science ®Google Scholar
• Yang Y. 2011. Performing wavelet based image fusion through different integration schemes. Int J Digit Content Technol Appl. 5:156–166.
   Google Scholar
• Yang B, Li S. 2012. Elsevier; Pixel-level image fusion with simultaneous orthogonal matching pursuit. J Inf Fusion. 13:10–19.
   Web of Science ®Google Scholar
• Yan YH, Li L, Yang YZ. 2012. Image fusion based on principal component analysis in dual-tree complex wavelet transform domainIn: Proceedings of International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP). 70–73.
   Google Scholar
• Yong Y, Dongsun P, Shuying H, Nini R. 2010. Medical image fusion via an effective wavelet-based approach. EURASIP J Adv Sign Process. 2010:1–13.
   Google Scholar
• Zhang Y, Hong G. 2005. Elsevier; An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images. Inf Fusion. 6:225–234.
   Google Scholar
• Zheng Y, Essock EA, Hansen BC. 2004. An advanced image fusion algorithm based on wavelet transform: incorporation with PCA and morphological processing. Electron Imaging. 2004:177–187.
   Google Scholar
• ZhuZ, ChaiY, YinH, LiY, LiuZ. 2016. A novel dictionary learning approach for multi-modality medical image fusion. Neurocomputing. 214: 471–482.
   Web of Science ®Google Scholar