AI

Sparse and transferable three-dimensional dynamic vascular reconstruction for instantaneous diagnosis

  • Mézquita, ajv et al. Corporate clinical coronary artery and coronary atrocroc of the coronary arteries: a collective statement from the quantitative cardiovascular photography group. Nat. Reverend Cardol. 20696-714 (2023).

    The article of the scientific researcher from Google

  • Mahmoud, KD & Zijlstra, F. Thrombus ASPIRATION in acute myocardial infarction. Nat. Reverend Cardol. 13418-428 (2016).

    The article of the scientific researcher from Google

  • çimen, S., Goya, A., Grass, M. & Frangi, AF RecONSTRUCTION CORONAY FERTIES from X -ray Vascular imaging: review. Med. Anal image. 3246-68 (2016).

    The article of the scientific researcher from Google

  • Zhao, h. et al. Learning subject to self -supervision enables the rebuilding of 3D digital vascular imaging from the most -dimensional two -sided projection views: a multi -center study. MP Cell. 3100775 (2022).

    The article of the scientific researcher from Google

  • Feldkamp, ​​La, Davis, LC & Kress, JW Empression Cone-Beam algorithm. J. OPT. Suk. I am. A 1612 (1984).

    The article of the scientific researcher from Google

  • Neubauer, am et al. The clinical feasibility for the fully rebuilding of the automated 3D from the coronary coronary vascular imaging. circus. Cardiovasc. The break. 371-79 (2010).

    The article of the scientific researcher from Google

  • Liu, J. et al. 5D algorithm rebuilding the respiratory respiratory image of 4D cone. Reverse Probl. 31115007 (2015).

    Mathscinet Google Scholar article

  • Blondel, C., Malandain, G., Vaillant, R. & Ayache, N. Rebuilding the coronary arteries of an x ​​-ray rotation sequence. IEEE Trans. Med. Photography 25653-663 (2006).

    The article of the scientific researcher from Google

  • Unbelath, M., Taubmann, O., Hell, M., AcheNBACH, S. & Maier, A. Symmetry, OutBliers, and Geodesics in Coronary Enery Center RECONDRUCTION from rotating vessels. Med. physics. 445672-5685 (2017).

    The article of the scientific researcher from Google

  • Bnerjee, A. Et al. The cloud method for the point to rebuild the three -dimensional coronary trees from the unavailable vascular projections at the same time. IEEE Trans. Med. Photography 391278-1290 (2020).

    The article of the scientific researcher from Google

  • Christ, W. Et al. The quantitative analysis of the 3-D rebuilding model of the mitral artery from multiple vessels. IEEE Trans. Biomed. Engineer. 622079-2090 (2015).

    The article of the scientific researcher from Google

  • Yang, c. And others. Forming the external power of the deformed global threat and improvement to rebuild the 3D coronary artery. physics. Med. Biol. 59975-1003 (2014).

    The article of the scientific researcher from Google

  • Liao, R. , Look, d. int. J. Cardiovasc. Photography 26733-749 (2010).

    The article of the scientific researcher from Google

  • Zheng, S., Meying, T account. Med. Photography graphic. 34333-345 (2010).

    The article of the scientific researcher from Google

  • Yang, J., Wang, Y., LIU, Y., Tang, S. & Chen, WW IEEE Trans. Image process. 181563-1572 (2009).

    Mathscinet Google Scholar article

  • Christ, W., Yang, J., LIU, Y. & Wang, Y. Energy Consciptive Composition for Reinstipation of 3D Coronary Article. in The annual International Conference on IEEE Engineering in Medicine and Biology Association 5151-5154 (IEEE, 2013).

  • Galasi, F. And others. Reconstruction of three -dimensional arteries of dual -dimensional vascular projections using the NORBS of the microscopic modeling of coronary embodiment. Plos one 13E0190650 (2018).

    The article of the scientific researcher from Google

  • Huang, M. And others. A simple way to automatic 3D reconstruction of coronary arteries from X -ray vessels. before. Physiol. 12724216 (2021).

    The article of the scientific researcher from Google

  • Bransby, km et al. Reconstruction of the 3D coronary vessel from dual -floor vessels using “graph” networks. in IEEE International Seminar on Biological Medical Photography 1-5 (IEEE, 2023).

  • Wang, G., Yee, JC & De Man, B. Deep Learning to rebuild cut images. Nat. Mach. Minds. 2737-748 (2020).

    The article of the scientific researcher from Google

  • IYER, K., Nallamothu, BK, Figueroa, Ca & Nadakuditi, RR Personal Nerve Regulations for Coronary Recalvation 3D from non -calibration X -ray vessels. Sci. representative. 1317603 (2023).

    The article of the scientific researcher from Google

  • Liang, D. & Chen, S. Preprint in Research field https://doi.org/10.21203/rs.3.RS-3703340/V1 (2023).

  • Gao, C. Et al. Artificial data speeds up the development of learning -learning algorithms to analyze X -ray images. Nat. Mach. Minds. 5294-308 (2023).

    The article of the scientific researcher from Google

  • Ying, x. et al. X2CT-Van: CT rebuild from Biplaanar X-ray with gynecological rivalry networks. in Brook. IEEE/CVF conference on computer vision and patterns 10619-10628 (IEEE, 2019).

  • KASTEN, Y., DOKTOFSKY, D. & Kovler, I.. The Tawarifi Nerve Network from Torde to Top to rebuild the knee bones of X -ray x -ray images. in An international workshop on machine learning to rebuild medical images 123-133 (Springer, 2020).

  • Kini, A. & Sharma, SK (EDS) A practical guide for interventional heart disease (Springer, 2021).

  • Graham, b. , Angeli, m. in Brook. IEEE/CVF conference on computer vision and patterns 9224-9232 (IEEE, 2018).

  • Shen, L., Zhao, W. & Xing, L. Reconstruction of the patient with the composed cut off from the display of one projection via deep learning. Nat. Biomed. Engineer. 3880-888 (2019).

    The article of the scientific researcher from Google

  • LI, M., Yang, H. & Kudo, H. The accurate re -construction algorithm of separate organisms: Apply to the rebuilding of 3D blood vessels of a limited number of expectations. physics. Med. Biol. 472599 (2002).

    The article of the scientific researcher from Google

  • Hansis, E. IEEE Trans. Med. Photography 271548-1555 (2008).

    The article of the scientific researcher from Google

  • Jandt, U., Schäfer, D., Grass, M. & Rasche, V. Generation Officative of 3D coronary artery lines using rotational X -ray vessels. Med. Anal image. 13846-858 (2009).

    The article of the scientific researcher from Google

  • Unbelath, M. Et al. Performing the movement of the respiratory system in rotating vessels: the improvement of the graphic model for automatic concentration measures. in IEEE International Seminar on Biological Medical Photography 227-230 (IEEE, 2017).

  • Antiga, L., ENE-RORDACHE, B. & Remuzzi, A. Massion Engineering for Patient Recalvation and Linking Vascular from MR and CT vascular imaging. IEEE Trans. Med. Photography 22674-684 (2003).

    The article of the scientific researcher from Google

  • Zheng, J.-Q. , Zhou, x.-y. , Riga, C. & Yang, G.-Z. Towards 3D planning of the path of one image of two -dimensional fluorine to remove the amazing vascular aortic artery. in International Conference on robots and automation 8747-8753 (IEEE, 2019).

  • Sumner, RW, Schmid, J ACM Trans. graph. 2680 (2007).

    The article of the scientific researcher from Google

  • HABERT, S., HABERT, S., Dahdah, N. & Cheriet, F. A new method for automatic 3D reconstruction of coronary arteries from vascular images. in International Conference on Information Sciences and Signal Processing and Applications 484-489 (IEEE, 2012).

  • Cinnamon, S. And others. CLDICE- The New Topology Loss to keep the tube installation fragmentation. in Brook. IEEE/CVF conference on computer vision and patterns 16560-16569 (IEEE, 2021).

  • Royer-Rivard, R., Girard, F., Dahdah, N. & Cheriet, F. P. deep-learning model for the synchronization of the heart cycle of multiple vascular serials. in The annual International Conference on IEEE Engineering in Medicine and Biology Association 1190-1193 (IEEE, 2020).

  • Vlontzos, A. & MikolajCKYK, K. Deep retail and registration in X -ray vascular video. in British automated vision conference 267-278 (BMVA, 2018).

  • Schonberger, JL & FRHM, J.-M. Burning of the movement to reconsider. in Brook. IEEE/CVF conference on computer vision and patterns 4104-4113 (IEEE, 2016).

  • Yu, T. And others. Doublefusion: Picking human performances in an actual time with the inner body shapes of a single depth sensor. IEEE Trans. Anal pattern. Mach. Minds. 422523-2539 (2019).

    The article of the scientific researcher from Google

  • Rohkohl, C., LAURISICH, G., Keil, A. & Hornegger, J physics. Med. Biol. 552905 (2010).

    The article of the scientific researcher from Google

  • Zeng, A. Et al. ImageCAS: A wide range of data set and a standard retail standard based on pictures of vessel imaging tomography. account. Med. Photography graphic. 109102287 (2023).

    The article of the scientific researcher from Google

  • Antiga, L., ENE-RORDACHE, B., Remzzzi, G. & Remuzzi, A. The automatic generation of Kabbi Tobology. Microvasc. Accuracy. 62346-354 (2001).

    The article of the scientific researcher from Google

  • Hartley, R. And Zisserman, a. View multiple engineering in your computer vision (Cambridge Press University, 2003).

  • Ravi, n. And others. Speeding the deep 3D learning with Pytorch3d. Preprint at https://arxiv.org/abs/2007.08501 (2020).

  • RIBA, E., Mishkin, D., Ponsa, D., Roblee, E. & Bradski, G. Kornia: A Open Source Diversion Vise Vision Vise Librance for pytorch. in Brook. IEEE/CVF Winter Conference on Computer Vision Applications 3674-3683 (IEEE, 2020).

  • NELL, a. in European Conference on Computer Vision 483-499 (2016).

  • GWAK, J., Choy, C. & Savarese, S. Different Discovery Networks to detect 3D objects. in European Conference on Computer Vision 297-313 (2020).

  • Zhu, y. et al. Reconstruction of 3D blood vessels scattered and convertable for immediate diagnosis. Zenudo https://doi.org/10.5281/zenodo.15004536 (2025).

  • Don’t miss more hot News like this! AI/" target="_blank" rel="noopener">Click here to discover the latest in AI news!

    2025-04-21 00:00:00

    Related Articles

    Back to top button