Abstract
Computed Tomography (CT) is a commonly used imaging modality across a wide variety of diagnostic procedures (World Health Organisation 2017). By generating contiguous cross-sectional images of a body region, CT has the ability to represent valuable 3D data that enables professionals to easily identify, locate, and accurately describe anatomical landmarks. Based on 3D modeling techniques developed by the field of Computer Graphics, the Region of Interest (ROI) can be extracted from the 2D anatomical slices and used to reconstruct subject-specific 3D models. This chapter describes a 3D reconstruction pipeline that can be used to generate 3D models from CT images and also volume renderings for medical visualization purposes (Ribeiro et al. 2009). We will provide several examples on how to segment 3D anatomical structures with high-contrast detail, namely skull, mandible, trachea, and colon, relying solely on the following set of free and open-source tools: ITK-SNAP (Yushkevich et al. 2006) and ParaView (Ahrens et al. 2005).
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References
Ahrens J, Geveci B, Law C (2005) ParaView: an end-user tool for large-data visualization. Vis Handb 717–731. https://doi.org/10.1016/b978-012387582-2/50038-1
Arora R, Kazi RH, Anderson F, Grossman T, Singh K, Fitzmaurice G (2017) Experimental evaluation of sketching on surfaces in VR. In: Conference on human factors in computing systems—proceedings, vol 2017, May 2017, pp 5643–5654. https://doi.org/10.1145/3025453.3025474
Barata G, Gama S, Jorge J, Gonçalves D (2013) So fun it hurts—Gamifying an engineering course. In: Schmorrow DD, Fidopiastis CM (eds) Foundations of augmented cognition. AC 2013. Lecture notes in computer science, vol 8027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39454-6_68
Blender Online Community, Blender project—Free and Open 3D Creation Software. https://www.blender.org/. Accessed 17 Jun 2020
Bohari U, Chen TJ, Vinayak (2018) To draw or not to draw: recognizing stroke-hover intent in non-instrumented gesture-free mid-air sketching. In: International conference on intelligent user interfaces, proceedings IUI, March 2018, pp 177–188. https://doi.org/10.1145/3172944.3172985
Clark K et al (2013) The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository. J Digit Imaging 26(6):1045–1057. https://doi.org/10.1007/s10278-013-9622-7
Coffey D et al (2012) Interactive slice WIM: Navigating and interrogating volume data sets using a multisurface, multitouch VR interface. IEEE Trans Vis Comput Graph 18(10):1614–1626. https://doi.org/10.1109/TVCG.2011.283
Duratti L, Wang F, Samur E, Bleuler H (2008) A real-time simulator for interventional radiology. In: Proceedings of the ACM symposium on virtual reality software and technology, VRST, 2008, pp 105–108. https://doi.org/10.1145/1450579.1450602
Figueiredo Paulo S, Figueiredo N, Armando Jorge J, Simões Lopes D (2018a) 3D reconstruction of CT colonography models for VR/AR applications using free software tools, Granada. https://miccai-sb.github.io/materials.html#mec2018. Accessed 17 June 2020
Figueiredo Paulo S, Belo M, Kuffner dos Anjos R, Armando Jorge J, Simões Lopes D (2018b) Volume and surface rendering of 3D medical datasets in unity®, Granada. https://miccai-sb.github.io/materials.html#mec2018. Accessed 17 June 2020
Heckel F, Moltz JH, Tietjen C, Hahn HK (2013) Sketch-based editing tools for tumour segmentation in 3d medical images. Comput Graph Forum 32(8):144–157. https://doi.org/10.1111/cgf.12193
Jackson B, Keefe DF (2016) Lift-off: using reference imagery and freehand sketching to create 3D models in VR. IEEE Trans Vis Comput Graph 22(4):1442–1451. https://doi.org/10.1109/TVCG.2016.2518099
John NW, McCloy RF (2004) Navigating and visualizing three-dimensional data sets. Br J Radiol 77(suppl2):S108–S113. https://doi.org/10.1259/bjr/45222871
Johnson CD et al (2008) Accuracy of CT colonography for detection of large adenomas and cancers. N Engl J Med 359(12):1207–1217. https://doi.org/10.1056/NEJMoa0800996
Johnson S, Erdman AG, Jackson B, Keefe DF, Tourek B, Molina M (2016) Immersive analytics for medicine: hybrid 2D/3D sketch-based interfaces for annotating medical data and designing medical devices. In: Companion proceedings of the 2016 ACM international conference on interactive surfaces and spaces: nature meets interactive surfaces, ISS 2016, November 2016, pp 107–113. https://doi.org/10.1145/3009939.3009956
Kroes T, Post FH, Botha CP (2012) Exposure render: an interactive photo-realistic volume rendering framework. PLoS One 7(7):e38586. https://doi.org/10.1371/journal.pone.0038586
Lopes DS et al (2018a) Interaction techniques for immersive CT colonography: a professional assessment. In: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), vol 11071, September 2018, pp 629–637. https://doi.org/10.1007/978-3-030-00934-2_70
Lopes DS et al (2018b) Explicit design of transfer functions for volume-rendered images by combining histograms, thumbnails, and sketch-based interaction. Vis Comput 34(12):1713–1723. https://doi.org/10.1007/s00371-017-1448-8
Lorensen WE, Cline HE (1987) Marching cubes: a high resolution 3D surface construction algorithm. ACM SIGGRAPH Comput Graph 21(4):163–169. https://doi.org/10.1145/37402.37422
Mendes D, Fonseca F, Araùjo B, Ferreira A, Jorge J (2014) Mid-air interactions above stereoscopic interactive tables. In: 2014 IEEE symposium on 3D User Interfaces (3DUI), Minneapolis, MN, pp 3–10. https://doi.org/10.1109/3DUI.2014.6798833
Meyer-Spradow J, Ropinski T, Mensmann J, Hinrichs K (2009) Voreen: a rapid-prototyping environment for ray-casting-based volume visualizations. IEEE Comput Graph Appl 29(6):6–13. https://doi.org/10.1109/MCG.2009.130
Mühler K, Tietjen C, Ritter F, Preim B (2010) The mduedical exploration toolkit: an efficient support for visual computing in surgical planning and training. IEEE Trans Vis Comput Graph 16(1):133–146. https://doi.org/10.1109/TVCG.2009.58
National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC), Radiology data from the clinical proteomic tumor analysis consortium pancreatic ductal adenocarcinoma [CPTAC-PDA] Collection [Data set]. Cancer Imag Arch. https://doi.org/10.7937/k9/tcia.2018.sc20fo18
Olabarriaga SD, Smeulders AWM (2001) Interaction in the segmentation of medical images: a survey. Med Image Anal 5(2):127–142. https://doi.org/10.1016/S1361-8415(00)00041-4
Olsen L, Samavati FF, Sousa MC, Jorge JA (2009) Sketch-based modeling: a survey. Comput Graph 33(1):85–103. https://doi.org/10.1016/j.cag.2008.09.013
Paulo SF et al (2018) The underrated dimension: How 3D interactive mammography can improve breast visualization. Lect Notes Comput Vis Biomech 27:329–337. https://doi.org/10.1007/978-3-319-68195-5_36
Peng H et al (2014) Virtual finger boosts three-dimensional imaging and microsurgery as well as terabyte volume image visualization and analysis. Nat Commun 5(1):1–13. https://doi.org/10.1038/ncomms5342
Ribeiro NS et al (2009) 3-D solid and finite element modeling of biomechanical structures- a software pipeline. In: Proceedings of the 7th EUROMECH Solid Mechanics Conference (ESMC2009), September 2009. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.544.2385. Accessed 17 June 2020
Robison RA, Liu CY, Apuzzo MLJ (2011) Man, mind, and machine: the past and future of virtual reality simulation in neurologic surgery. World Neurosurg 76(5):419–430. https://doi.org/10.1016/j.wneu.2011.07.008
Rosset A, Spadola L, Ratib O (2004) OsiriX: an open-source software for navigating in multidimensional DICOM images. J Digit Imaging 17(3):205–216. https://doi.org/10.1007/s10278-004-1014-6
Shepherd T, Prince SJD, Alexander DC (2012) Interactive lesion segmentation with shape priors from offline and online learning. IEEE Trans Med Imaging 31(9):1698–1712. https://doi.org/10.1109/TMI.2012.2196285
Smith K et al., Data from CT colonography. Cancer Imag Arch https://doi.org/10.7937/K9/TCIA.2015.NWTESAY1
Sousa M, Mendes D, Paulo S, Matela N, Jorge J, Lopes DS (2017) VRRRRoom: virtual reality for radiologists in the reading room. In: Conference on human factors in computing systems—proceedings, vol 2017, May 2017, pp 4057–4062. https://doi.org/10.1145/3025453.3025566
Van Heeswijk MM et al (2016) Automated and semiautomated segmentation of rectal tumor volumes on diffusion-weighted MRI: can it replace manual volumetry? Int J Radiat Oncol Biol Phys 94(4):824–831. https://doi.org/10.1016/j.ijrobp.2015.12.017
Viceconti M, Taddei F (2003) Automatic generation of finite element meshes from computed tomography data. Crit Rev Biomed Eng 31(1–2):27–72. https://doi.org/10.1615/CritRevBiomedEng.v31.i12.20
Vosburgh KG, Golby A, Pieper SD (2013) Surgery, virtual reality, and the future. Stud Health Technol Inform 184:vii–xiii. http://www.ncbi.nlm.nih.gov/pubmed/23653952. Accessed 22 June 2020
World Health Organisation, Global atlas of medical devices, no. Licence: CC BY-NC-SA 3.0 IGO. 2017
Yushkevich PA et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31(3):1116–1128. https://doi.org/10.1016/j.neuroimage.2006.01.015
Zorzal E, Gomes J, Sousa M, Belchior P, Silva P, Figueiredo N, Lopes D, Jorge J (2020) Laparoscopy with augmented reality adaptations. J Biomed Inform 107:103463. ISSN 1532-0464, https://doi.org/10.1016/j.jbi.2020.103463
Acknowledgments
All authors are thankful for the financial support given by Portuguese Foundation for Science and Technology (FCT). In particular, the first author thanks for the doctoral grant SFRH/BD/136212/2018. This work was also partially supported by national funds through FCT with reference UID/CEC/50021/2019 and IT-MEDEX PTDC/EEI-SII/6038/2014.
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Paulo, S.F., Lopes, D.S., Jorge, J. (2021). 3D Reconstruction from CT Images Using Free Software Tools. In: Uhl, JF., Jorge, J., Lopes, D.S., Campos, P.F. (eds) Digital Anatomy . Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-030-61905-3_8
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