دانشگاه مازندران

 Statistics

Number of Journals32
Number of Issues554
Number of Articles5,380
Article View8,161,418
PDF Download6,064,433
(2025). . Journal of Executive Management, 2(3), 18-25. doi: 10.22080/cste.2025.29117.1040
. "". Journal of Executive Management, 2, 3, 2025, 18-25. doi: 10.22080/cste.2025.29117.1040
(2025). '', Journal of Executive Management, 2(3), pp. 18-25. doi: 10.22080/cste.2025.29117.1040
. Journal of Executive Management, 2025; 2(3): 18-25. doi: 10.22080/cste.2025.29117.1040

Contributions of Science and Technology for Engineering
Article 5, Volume 2, Issue 3, January 0, Pages 18-25    PDF (746.17 K)
Document Type: Original Article
DOI: 10.22080/cste.2025.29117.1040
Receive Date: 28 April 2025,  Revise Date: 20 May 2025,  Accept Date: 20 May 2025 
Supplementary Files
References
  1. Velesaca, H. O., Bastidas, G., Rouhani, M., & Sappa, A. D. (2024). Multimodal image registration techniques: a comprehensive survey. Multimedia Tools and Applications, 83(23), 63919–63947. doi:10.1007/s11042-023-17991-2.
  2. Jena, R., Sethi, D., Chaudhari, P., & Gee, J. (2024). Deep learning in medical image registration: Magic or mirage?. 38th Conference on Neural Information Processing Systems (NeurIPS 2024), 37, 108331-108353, 9-15, December, 2024, Vancouver, Canada.
  3. Ahir, B. K., Engelhard, H. H., & Lakka, S. S. (2020). Tumor Development and Angiogenesis in Adult Brain Tumor: Glioblastoma. Molecular Neurobiology, 57(5), 2461–2478. doi:10.1007/s12035-020-01892-8.
  4. Jalalzadeh, A. H., Shalbaf, A., & Maghsoudi, A. (2021). Compensation of brain shift during surgery using non-rigid registration of MR and ultrasound images. Tehran University Medical Journal, 78(10), 658–667. http://tumj.tums.ac.ir/article-1-10930-en.html.
  5. Xiao, Y., Fortin, M., Unsgärd, G., Rivaz, H., & Reinertsen, I. (2017). REtroSpective Evaluation of Cerebral Tumors (RESECT): A clinical database of pre-operative MRI and intra-operative ultrasound in low-grade glioma surgeries: A. Medical Physics, 44(7), 3875–3882. doi:10.1002/mp.12268.
  6. Avants, B. B., Epstein, C. L., Grossman, M., & Gee, J. C. (2008). Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1), 26–41. doi:10.1016/j.media.2007.06.004.
  7. Mani, V. R. S., & Arivazhagan, S. (2013). Survey of medical image registration. Journal of Biomedical Engineering and Technology, 1(2), 8-25.
  8. Balasamy, K., Seethalakshmi, V., & Suganyadevi, S. (2024). Medical Image Analysis Through Deep Learning Techniques: A Comprehensive Survey. Wireless Personal Communications, 137(3), 1685–1714. doi:10.1007/s11277-024-11428-1.
  9. Chen, J., Liu, Y., Wei, S., Bian, Z., Subramanian, S., Carass, A., Prince, J. L., & Du, Y. (2025). A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond. Medical Image Analysis, 100, 103385. doi:10.1016/j.media.2024.103385.
  10. Ramadan, H., El Bourakadi, D., Yahyaouy, A., & Tairi, H. (2024). Medical image registration in the era of Transformers: A recent review. Informatics in Medicine Unlocked, 49, 101540. doi:10.1016/j.imu.2024.101540.
  11. Tang, K., Li, Z., Tian, L., Wang, L., & Zhu, Y. (2020). ADMIR-Affine and deformable medical image registration for drug-addicted brain images. IEEE Access, 8, 70960–70968. doi:10.1109/ACCESS.2020.2986829.
  12. Mok, T.C.W., & Chung, A.C.S. (2020). Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12263. Springer, Cham, Switzerland. doi:10.1007/978-3-030-59716-0_21.
  13. Kim, B., Han, I., & Ye, J.C. (2022). DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model. Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13691. Springer, Cham, Switzerland. doi:10.1007/978-3-031-19821-2_20.
  14. Mok, T. C. W., & Chung, A. C. S. (2020). Fast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr42600.2020.00470.
  15. Jia, X., Bartlett, J., Zhang, T., Lu, W., Qiu, Z., Duan, J. (2022). U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?. Machine Learning in Medical Imaging. MLMI 2022. Lecture Notes in Computer Science, vol 13583. Springer, Cham, Switzerland. doi:10.1007/978-3-031-21014-3_16.
  16. Pielawski, N., Wetzer, E., Öfverstedt, J., Lu, J., Wählby, C., Lindblad, J., & Sladoje, N. (2020). CoMIR: Contrastive multimodal image representation for registration. Advances in neural information processing systems, 33, 18433-18444.
  17. Jalalzadeh, A. H., Talebi, S. S., & Kamangar, M. H. (2024). Two-step registration of rigid and non-rigid MR-iUS for brain shift compensation using transfer learning. 2024 20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024, 1–5,. doi:10.1109/AISP61396.2024.10475261.
  18. Dalca, A. V., Balakrishnan, G., Guttag, J., & Sabuncu, M. R. (2019). Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces. Medical Image Analysis, 57, 226–236. doi:10.1016/j.media.2019.07.006.
  19. Balakrishnan, G., Zhao, A., Sabuncu, M. R., Guttag, J., & Dalca, A. V. (2019). VoxelMorph: A Learning Framework for Deformable Medical Image Registration. IEEE Transactions on Medical Imaging, 38(8), 1788–1800. doi:10.1109/tmi.2019.2897538.
  20. Mercier, L., Del Maestro, R. F., Petrecca, K., Araujo, D., Haegelen, C., & Collins, D. L. (2012). Online database of clinical MR and ultrasound images of brain tumors. Medical Physics, 39(6), 3253–3261. doi:10.1118/1.4709600.
  21. Tustison, N. J., Yassa, M. A., Rizvi, B., Cook, P. A., Holbrook, A. J., Sathishkumar, M. T., Tustison, M. G., Gee, J. C., Stone, J. R., & Avants, B. B. (2024). ANTsX neuroimaging-derived structural phenotypes of UK Biobank. Scientific Reports, 14(1), 8848. doi:10.1038/s41598-024-59440-6.
  22. Tustison, N. J., Cook, P. A., Holbrook, A. J., Johnson, H. J., Muschelli, J., Devenyi, G. A., Duda, J. T., Das, S. R., Cullen, N. C., Gillen, D. L., Yassa, M. A., Stone, J. R., Gee, J. C., & Avants, B. B. (2021). The ANTsX ecosystem for quantitative biological and medical imaging. Scientific Reports, 11(1), 9068. doi:10.1038/s41598-021-87564-6.
  23. Avants, B. B., Tustison, N. J., Song, G., Cook, P. A., Klein, A., & Gee, J. C. (2011). A reproducible evaluation of ANTs similarity metric performance in brain image registration. NeuroImage, 54(3), 2033–2044. doi:10.1016/j.neuroimage.2010.09.025.
  24. Razlighi, Q. R., Kehtarnavaz, N., & Yousefi, S. (2013). Evaluating similarity measures for brain image registration. Journal of Visual Communication and Image Representation, 24(7), 977–987. doi:10.1016/j.jvcir.2013.06.010.
Statistics
Article View: 208
PDF Download: 189


Journal Management System. Powered by Sinaweb