3D Medical Segmentation Visualization in Julia with MedEye3d

• Autorzy: Mitura Jakub , Chrapko Beata E.

Identyfikatory

DOI

10.26348/znwwsi.25.57

• Języki publikacji: EN

Abstrakty

EN

MedEye3d is a Julia language package designed to simplify visualizations of segmentation in three dimensional setting. Motivation to develop this application was to provide to rapidly growing Julia language scientific community tool for research in three dimensional medical images. Package is based on multiple open source software packages, yet most prominent is utilization of OpenGl specification to enable GPU acceleration. Application was tested both on Linux and Windows platforms and in both cases latency observed by the user in most common interaction like scrolling, annotation and change of displayed plane was very small. Thanks to utilization of many modern packages and methodologies developed package is providing convenient visualization in rapid prototyping with medical image segmentation algorithms. Application also is easily extendable and will be included in medical image segmentation framework that is currently in development.

Słowa kluczowe

EN

OpenGl; Computer Tomography; PET/CT; medical image annotation; medical image visualization

• Wydawca: Warszawska Wyższa Szkoła Informatyki
• Czasopismo: Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
• Rocznik: 2021
• Tom: nr 25
• Strony: 57--67
• Opis fizyczny: Bibliogr. 17 poz., fot., wykr.

Twórcy

autor

Mitura Jakub

• Medical University of Lublin

autor

Chrapko Beata E.

• Chair and Department of Nuclear Medicine, Medical University of Lublin

Bibliografia

• [1] J. Bertels, T. Eelbode, M. Berman, D. Vandermeulen, F. Maes, R. Bisschops, and M. B. Blaschko, “Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice,” in Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, D. Shen, T. Liu, T. M. Peters, L. H. Staib, C. Essert, S. Zhou, P.-T. Yap, and A. Khan, Eds. Cham: Springer International Publishing, 2019, pp. 92-100. [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-030-32245-8 11
• [2] A. M. Loening and S. S. Gambhir, “AMIDE: A Free Software Tool for Multimodality Medical Image Analysis,” Molecular Imaging, vol. 2, no. 3, pp. 131-137, 2003. [Online]. Available: https://doi.org/10.1162/15353500200303133
• [3] R. Kikinis, S. D. Pieper, and K. G. Vosburgh, 3D Slicer: A Platform for Subject-Specific Image Analysis, Visualization, and Clinical Support. New York, NY: Springer New York, 2014, pp. 277-289. [Online]. Available: https://doi.org/10.1007/978-1-4614-7657-3 19
• [4] J. Bezanson, A. Edelman, S. Karpinski, and V. B. Shah, “Julia: A fresh approach to numerical computing,” SIAM review, vol. 59, no. 1, pp. 65-98, 2017. [Online]. Available: https://doi.org/10.1137/141000671
• [5] M. Woo, J. Neider, T. Davis, and D. Shreiner, OpenGL programming guide: the official guide to learning OpenGL, version 1.2. Addison-Wesley Longman Publishing Co., Inc., 1999.
• [6] SimonDanisch, rennis250, and o jasper, “ModernGL.jl,” 2021. [Online]. Available: https://github.com/JuliaGL/ModernGL.jl
• [7] SimonDanisch and aaalexandrov, “FreeTypeAbstraction.jl,” 2021. [Online]. Available: https://github.com/JuliaGraphics/FreeTypeAbstraction.jl
• [8] jorge brito, “Glutils.jl,” 2021. [Online]. Available: https://github.com/jorge-brito/Glutils.jl
• [9] D. Bagaev, “Rocket.jl,” 2021. [Online]. Available: https://github.com/biaslab/Rocket.jl
• [10] A. Ferris, “Dictionaries.jl,” 2021. [Online]. Available: https://github.com/andyferris/ Dictionaries.jl
• [11] Mauro, “Parameters.jl,” 2021. [Online]. Available: https://github.com/mauro3/Parameters.jl
• [12] J. Weidner, “Setfield.jl,” 2021. [Online]. Available: https://github.com/jw3126/Setfield.jl
• [13] K. Squire, “Match.jl,” 2021. [Online]. Available: https://github.com/kmsquire/Match.jl
• [14] G. Datseris, J. Isensee, S. Pech, and T. Gál, “DrWatson: the perfect sidekick for your scientific inquiries,” Journal of Open Source Software, vol. 5, no. 54, p. 2673, 2020. [Online]. Available: https://doi.org/10.21105/joss.02673
• [15] T. Heimann, B. van Ginneken, and M. Styner, “SILVER07,” 2021. [Online]. Available: http://www.sliver07.org/
• [16] M. Vallieres, E. Kay-Rivest, L. J. Perrin, X. Liem, C. Furstoss, H. J. W. L. Aerts, N. Khaouam, P. F. Nguyen-Tan, C.-S. Wang, K. Sultanem et al., “Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer,” Scientific reports, vol. 7, no. 1, pp. 1-14, 2017. [Online]. Available: https://doi.org/10.1038/s41598-017-10371-5
• [17] J. Revels, “BenchmarkTools.jl,” 2021. [Online]. Available: https://github.com/JuliaCI/BenchmarkTools.jl