Hybrid Optical Scanning Holography for Automatic Three-Dimensional Reconstruction of Brain Tumors from MRI using Active Contours

Volume 9, Issue 4, Page No 07-13, 2024

Author’s Name: Abdennacer El-Ouarzadi¹, Anass Cherkaoui¹, Abdelaziz Essadike², Abdenbi Bouzid¹

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¹ Moulay Ismail University, Physical Sciences and Engineering, Faculty of Sciences, Meknès, 11201, Morocco
²Hassan First University of Settat, Higher Institute of Health Sciences, Laboratory of Health Sciences and Technologies, Settat, 26000, Morocco

^a)whom correspondence should be addressed. E-mail: a.elouarzadi@edu.umi.ac.ma

Adv. Sci. Technol. Eng. Syst. J. 9(4), 07-13 (2024); DOI: 10.25046/aj090402

Keywords: Bain tumor detection, Fully Automatic Segmentation, Active contour, Optical Scanning Holography (OSH), 3D Automatic Reconstruction

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Abstract

This paper presents a method for automatic 3D segmentation of brain tumors in MRI using optical scanning holography. Automatic segmentation of tumors from 2D slices (coronal, sagittal and axial) enables efficient 3D reconstruction of the region of interest, eliminating the human errors of manual methods. The method uses enhanced optical scanning holography with a cylindrical lens, scanning line by line, and displays MRI images via a spatial light modulator. The outgoing phase component of the scanned data, collected digitally, reliably indicates the position of the tumor.The tumor position is fed into an active contour model (ACM), which speeds up segmentation of the seeding region. The tumor is then reconstructed in 3D from the segmented regions in each slice, enabling tumor volume to be calculated and cancer progression to be estimated. Experiments carried out on patient MRI datasets show satisfactory results. The proposed approach can be integrated into a computer-aided diagnosis (CAD) system, helping doctors to localize the tumor, estimate its volume and provide 3D information to improve treatment techniques such as radiosurgery, stereotactic surgery or chemotherapy administration. In short, this method offers a precise and reliable solution for the segmentation and 3D reconstruction of brain tumors, facilitating diagnosis and treatment.

Received: 03 May 2024, Revised: 26 June 2024, Accepted: 27 June 2024, Published Online: 10 July 2024

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References (48)

T.J. Hudson, “The International Cancer Genome Consortium,” Cancer Research, 176(1), 139–148, 2009, doi:10.1038/nature08987.International.
S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J.S. Kirby, J.B. Freymann, K. Farahani, C. Davatzikos, “Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features,” Scientific Data, 4(1), 170117, 2017, doi:10.1038/sdata.2017.117.
R. Ranjbarzadeh, A. Bagherian Kasgari, S. Jafarzadeh Ghoushchi, S. Anari, M. Naseri, M. Bendechache, “Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images,” Scientific Reports, 11(1), 10930, 2021, doi:10.1038/s41598-021-90428-8.
R.P.J., “BRAIN TUMOR MRI IMAGE SEGMENTATION AND DETECTION IN IMAGE PROCESSING,” International Journal of Research in Engineering and Technology, 03(13), 1–5, 2014, doi:10.15623/ijret.2014.0313001.
B.H. Menze, A. Jakab, S. Bauer, J. Kalpathy-Cramer, K. Farahani, J. Kirby, Y. Burren, N. Porz, J. Slotboom, R. Wiest, L. Lanczi, E. Gerstner, M.-A. Weber, T. Arbel, B.B. Avants, N. Ayache, P. Buendia, D.L. Collins, N. Cordier, J.J. Corso, A. Criminisi, T. Das, H. Delingette, C. Demiralp, C.R. Durst, M. Dojat, S. Doyle, J. Festa, F. Forbes, et al., “The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS),” IEEE Transactions on Medical Imaging, 34(10), 1993–2024, 2015, doi:10.1109/TMI.2014.2377694.
The Efficiency of 3D-Printed Dog Brain Ventricular Models from 3 Tesla (3T) Magnetic Resonance Imaging (MRI) for Neuroanatomy Education, The Pakistan Veterinary Journal, 2024, doi:10.29261/pakvetj/2024.168.
M. Bartels, M. Priebe, R.N. Wilke, S.P. Krüger, K. Giewekemeyer, S. Kalbfleisch, C. Olendrowitz, M. Sprung, T. Salditt, “Low-dose three-dimensional hard x-ray imaging of bacterial cells,” Optical Nanoscopy, 1(1), 10, 2012, doi:10.1186/2192-2853-1-10.
K. Pawar, Z. Chen, N. Jon Shah, G.F. Egan, An Ensemble of 2D Convolutional Neural Network for 3D Brain Tumor Segmentation, 359–367, 2020, doi:10.1007/978-3-030-46640-4_34.
M. kamal Al-anni, P. DRAP, “Efficient 3D Instance Segmentation for Archaeological Sites Using 2D Object Detection and Tracking,” International Journal of Computing and Digital Systems, 15(1), 1333–1342, 2024, doi:10.12785/ijcds/150194.
G. Gunasekaran, M. Venkatesan, “An Efficient Technique for Three-Dimensional Image Visualization Through Two-Dimensional Images for Medical Data,” Journal of Intelligent Systems, 29(1), 100–109, 2019, doi:10.1515/jisys-2017-0315.
H. Khan, S.F. Alam Zaidi, A. Safi, S. Ud Din, A Comprehensive Analysis of MRI Based Brain Tumor Segmentation Using Conventional and Deep Learning Methods, 92–104, 2020, doi:10.1007/978-3-030-43364-2_9.
V. Kumar, T. Lal, P. Dhuliya, D. Pant, “A study and comparison of different image segmentation algorithms,” in 2016 2nd International Conference on Advances in Computing, Communication, & Automation (ICACCA) (Fall), IEEE: 1–6, 2016, doi:10.1109/ICACCAF.2016.7749007.
M. Eliasof, A. Sharf, E. Treister, “Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods,” SIAM Journal on Imaging Sciences, 13(1), 265–290, 2020, doi:10.1137/19M1257895.
W.-W. Lin, C. Juang, M.-H. Yueh, T.-M. Huang, T. Li, S. Wang, S.-T. Yau, “3D brain tumor segmentation using a two-stage optimal mass transport algorithm,” Scientific Reports, 11(1), 14686, 2021, doi:10.1038/s41598-021-94071-1.
P. Li, W. Wu, L. Liu, F. Michael Serry, J. Wang, H. Han, “Automatic brain tumor segmentation from Multiparametric MRI based on cascaded 3D U-Net and 3D U-Net++,” Biomedical Signal Processing and Control, 78, 103979, 2022, doi:10.1016/j.bspc.2022.103979.
D. GABOR, “A New Microscopic Principle,” Nature, 161(4098), 777–778, 1948, doi:10.1038/161777a0.
U. Schnars, W. Jüptner, “Direct recording of holograms by a CCD target and numerical reconstruction,” Applied Optics, 33(2), 179, 1994, doi:10.1364/AO.33.000179.
W. Xu, M.H. Jericho, I.A. Meinertzhagen, H.J. Kreuzer, “Digital in-line holography for biological applications,” Proceedings of the National Academy of Sciences, 98(20), 11301–11305, 2001, doi:10.1073/pnas.191361398.
P. Marquet, B. Rappaz, P.J. Magistretti, E. Cuche, Y. Emery, T. Colomb, C. Depeursinge, “Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy,” Optics Letters, 30(5), 468, 2005, doi:10.1364/OL.30.000468.
J. Garcia-Sucerquia, W. Xu, S.K. Jericho, P. Klages, M.H. Jericho, H.J. Kreuzer, “Digital in-line holographic microscopy,” Applied Optics, 45(5), 836, 2006, doi:10.1364/AO.45.000836.
E. Cuche, F. Bevilacqua, C. Depeursinge, “Digital holography for quantitative phase-contrast imaging,” Optics Letters, 24(5), 291, 1999, doi:10.1364/OL.24.000291.
B. Rappaz, P. Marquet, E. Cuche, Y. Emery, C. Depeursinge, P.J. Magistretti, “Measurement of the integral refractive index and dynamic cell morphometry of living cells with digital holographic microscopy,” Optics Express, 13(23), 9361, 2005, doi:10.1364/OPEX.13.009361.
B. Kemper, G. von Bally, “Digital holographic microscopy for live cell applications and technical inspection,” Applied Optics, 47(4), A52, 2008, doi:10.1364/AO.47.000A52.
N. Demoli, D. Vukicevic, M. Torzynski, “Dynamic digital holographic interferometry with three wavelengths,” Optics Express, 11(7), 767, 2003, doi:10.1364/OE.11.000767.
J. Zhao, H. Jiang, J. Di, “Recording and reconstruction of a color holographic image by using digital lensless Fourier transform holography,” Optics Express, 16(4), 2514, 2008, doi:10.1364/OE.16.002514.
P. Tankam, P. Picart, D. Mounier, J.M. Desse, J. Li, “Method of digital holographic recording and reconstruction using a stacked color image sensor,” Applied Optics, 49(3), 320, 2010, doi:10.1364/AO.49.000320.
F. Charrière, J. Kühn, T. Colomb, F. Montfort, E. Cuche, Y. Emery, K. Weible, P. Marquet, C. Depeursinge, “Characterization of microlenses by digital holographic microscopy,” Applied Optics, 45(5), 829, 2006, doi:10.1364/AO.45.000829.
J.-M. Desse, P. Picart, P. Tankam, “Digital three-color holographic interferometry for flow analysis,” Optics Express, 16(8), 5471, 2008, doi:10.1364/OE.16.005471.
P. Tankam, Q. Song, M. Karray, J. Li, J. Michel Desse, P. Picart, “Real-time three-sensitivity measurements based on three-color digital Fresnel holographic interferometry,” Optics Letters, 35(12), 2055, 2010, doi:10.1364/OL.35.002055.
K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R.R. Dasari, Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” Journal of Biomedical Optics, 19(01), 1, 2013, doi:10.1117/1.JBO.19.1.011005.
F. Yaraş, H. Kang, L. Onural, “Real-time phase-only color holographic video display system using LED illumination,” Applied Optics, 48(34), H48, 2009, doi:10.1364/AO.48.000H48.
P.-A. Blanche, A. Bablumian, R. Voorakaranam, C. Christenson, W. Lin, T. Gu, D. Flores, P. Wang, W.-Y. Hsieh, M. Kathaperumal, B. Rachwal, O. Siddiqui, J. Thomas, R.A. Norwood, M. Yamamoto, N. Peyghambarian, “Holographic three-dimensional telepresence using large-area photorefractive polymer,” Nature, 468(7320), 80–83, 2010, doi:10.1038/nature09521.
J. Geng, “Three-dimensional display technologies,” Advances in Optics and Photonics, 5(4), 456, 2013, doi:10.1364/AOP.5.000456.
M. Kujawinska, T. Kozacki, C. Falldorf, T. Meeser, B.M. Hennelly, P. Garbat, W. Zaperty, M. Niemelä, G. Finke, M. Kowiel, T. Naughton, “Multiwavefront digital holographic television,” Optics Express, 22(3), 2324, 2014, doi:10.1364/OE.22.002324.
H. Mukawa, K. Akutsu, I. Matsumura, S. Nakano, T. Yoshida, M. Kuwahara, K. Aiki, M. Ogawa, “8.4: Distinguished Paper : A Full Color Eyewear Display Using Holographic Planar Waveguides,” SID Symposium Digest of Technical Papers, 39(1), 89–92, 2008, doi:10.1889/1.3069819.
C. Jang, C.-K. Lee, J. Jeong, G. Li, S. Lee, J. Yeom, K. Hong, B. Lee, “Recent progress in see-through three-dimensional displays using holographic optical elements [Invited],” Applied Optics, 55(3), A71, 2016, doi:10.1364/AO.55.000A71.
I. Yamaguchi, Phase-Shifting Digital Holography, Springer US: 145–171, 2006, doi:10.1007/0-387-31397-4_5.
I. Yamaguchi, J. Kato, S. Ohta, J. Mizuno, “Image formation in phase-shifting digital holography and applications to microscopy,” Applied Optics, 40(34), 6177, 2001, doi:10.1364/AO.40.006177.
F. Le Clerc, L. Collot, M. Gross, “Numerical heterodyne holography with two-dimensional photodetector arrays,” Optics Letters, 25(10), 716, 2000, doi:10.1364/OL.25.000716.
E. Absil, G. Tessier, M. Gross, M. Atlan, N. Warnasooriya, S. Suck, M. Coppey-Moisan, D. Fournier, “Photothermal heterodyne holography of gold nanoparticles,” Optics Express, 18(2), 780, 2010, doi:10.1364/OE.18.000780.
B. Samson, F. Verpillat, M. Gross, M. Atlan, “Video-rate laser Doppler vibrometry by heterodyne holography,” Optics Letters, 36(8), 1449, 2011, doi:10.1364/OL.36.001449.
T.-C. Poon, Three-dimensional image processing and optical scanning holography, 329–350, 2003, doi:10.1016/S1076-5670(03)80018-6.
Y. Zhang, R. Wang, P. Tsang, T.-C. Poon, “Sectioning with edge extraction in optical incoherent imaging processing,” OSA Continuum, 3(4), 698, 2020, doi:10.1364/OSAC.383473.
G. Indebetouw, W. Zhong, D. Chamberlin-Long, “Point-spread function synthesis in scanning holographic microscopy,” Journal of the Optical Society of America A, 23(7), 1708, 2006, doi:10.1364/JOSAA.23.001708.
X. Zhang, E.Y. Lam, “Edge detection of three-dimensional objects by manipulating pupil functions in an optical scanning holography system,” in 2010 IEEE International Conference on Image Processing, IEEE: 3661–3664, 2010, doi:10.1109/ICIP.2010.5652483.
Y. Momonoi, K. Taira, Y. Hirayama, “Scan-type image capturing system using a cylindrical lens for one-dimensional integral imaging,” in: Woods, A. J., Dodgson, N. A., Merritt, J. O., Bolas, M. T., and McDowall, I. E., eds., in Stereoscopic Displays and Virtual Reality Systems XIV, 649017, 2007, doi:10.1117/12.703170.
A. Cherkaoui, A. El-Ouarzadi, A. Essadike, Y. Achaoui, A. Bouzid, “Brain Tumor Detection and Segmentation Using a Hybrid Optical Method by Active Contour,” in 2023 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA), IEEE: 132–138, 2023, doi:10.1109/ICDATA58816.2023.00032.
A. EL-OUARZADI, A. Cherkaoui, A. Essadike, A. Bouzid, “Brain Tumor Detection and Segmentation Using a Hybrid Optical Method by Active Contour,” Available at SSRN 4629062, doi:10.2139/ssrn.4629062.

Hybrid Optical Scanning Holography for Automatic Three-Dimensional Reconstruction of Brain Tumors from MRI using Active Contours