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International Journal of Bioprinting                         Deep learning-based 3D digital model of fetal heart




            21.  Bradski G, Kaehler A. Learning OpenCV: Computer Vision   deep  learning  on  whole  slide  images.  Nat Med.
               with the OpenCV Library. Cambridge: O’Reilly; 2008.  2019;25(8):1301-1309.
               doi: 10.1109/MRA.2009.933612                       doi: 10.1038/s41591-019-0508-1
            22.  Bishop KC, Kuller JA, Boyd BK, Rhee EH, Miller S, Barker   26.  Litjens  G, Kooi T,  Bejnordi  BE, et  al.  A survey on  deep
               P. Ultrasound examination of the fetal heart. Obstet Gynecol   learning in medical image analysis.  Med Image Anal.
               Surv. 2017;72(1):54-61.
               doi: 10.1097/OGX.0000000000000394                  2017;42:60-88.
                                                                  doi: 10.1016/j.media.2017.07.005
            23.  Liu S, Wang Y, Yang X, et al. Deep learning in medical
               ultrasound analysis: a review. Engineering. 2019;5(2):261-275.  27.  Luijten B, Cohen R, de Bruijn FJ, et al. Adaptive ultrasound
               doi: 10.1016/j.eng.2018.11.020                     beamforming using deep learning. IEEE Trans Med Imaging.
                                                                  2020;39(12):3967-3978.
            24.  Ouyang D, He B, Ghorbani A, et al. Video-based AI for
               beat-to-beat assessment of cardiac function.  Nature.      doi: 10.1109/TMI.2020.3008537
               2020;580(7802):252-256.                         28.  Liaw CY, Guvendiren M. Current and emerging applications
               doi: 10.1038/s41586-020-2145-8                     of 3D printing in medicine.  Biofabrication. 2017;
            25.  Campanella G, Hanna MG, Geneslaw L, et al. Clinical-  9(2):024102.
               grade computational pathology using weakly supervised      doi: 10.1088/1758-5090/aa7279
























































            Volume 11 Issue 4 (2025)                       255                            doi: 10.36922/IJB025200192
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