Simultaneous Iterative Reconstruction Method for High Resolution X-Ray Phase-Contrast Tomography

被引:2
作者
Bukreeva, I [1 ,2 ]
Asadchikov, V [3 ]
Buzmakov, A. [3 ]
Chukalina, M. [3 ,4 ]
Ingacheva, A. [3 ,4 ]
Palermo, F. [1 ]
Fratini, M. [1 ,5 ]
Cedola, A. [1 ]
机构
[1] Inst Nanotechnol CNR, Rome Unit, Piazzale Aldo Moro 5, Rome, Italy
[2] RAS, PN Lebedev Phys Inst, Leninskii Pr 53, Moscow, Russia
[3] RAS, Shubnikov Inst Crystallog FSRC Crystallog & Photo, Leninskii Prosp 59, Moscow, Russia
[4] Inst Informat Transmiss Problems, B Koretnii Per 9, Moscow, Russia
[5] Fdn Santa Lucia IRCCS, Via Ardeatina 306, I-00179 Rome, Italy
来源
TWELFTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2019) | 2020年 / 11433卷
基金
欧盟地平线“2020”;
关键词
X-ray phase contrast micro tomography; spine; spinal cord; preclinical ex-vivo mouse model; PLATFORM; IMAGE;
D O I
10.1117/12.2557133
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Computer vision for biomedical imaging applications is fast developing and at once demanding field of computer science. In particular, computer vision technique provides excellent results for detection and segmentation problems in tomographic imaging. X-ray phase contrast Tomography (XPCT) is a noninvasive 3D imaging technique with high sensitivity for soft tissues. Despite a considerable progress in XPCT data acquisition and data processing methods, the problem in degradation of image quality due to artifacts remains a widespread and often critical issue for computer vision applications. One of the main problems originates from a sample alteration during a long tomographic scan. We proposed and tested Simultaneous Iterative Reconstruction algorithm with Total Variation regularization to reduce the number of projections in high resolution XPCT scans of ex-vivo mouse spinal cord. We have shown that the proposed algorithm allows tenfold reducing the number of projections and, therefore, the exposure time, with conservation of the important morphological information in 3D image with quality acceptable for computer graphics and computer vision applications. Our research paves a way for more effective implementation of advanced computer technologies in phase contrast tomographic research.
引用
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页数:7
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共 25 条
  • [1] [Anonymous], 2010, THEORY FOUND NUMER M
  • [2] Advanced x-ray tomography: experiment, modeling, and algorithms
    Batenburg, K. Joost
    De Carlo, Francesco
    Mancini, Lucia
    Sijbers, Jan
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2018, 29 (08)
  • [3] Reduction of variable-truncation artifacts from beam occlusion during in situ x-ray tomography
    Borg, Leise
    Jorgensen, Jakob S.
    Frikel, Juergen
    Sporring, Jon
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2017, 28 (12)
  • [4] Restoration of low-dose digital breast tomosynthesis
    Borges, Lucas R.
    Azzari, Lucio
    Bakic, Predrag R.
    Maidment, Andrew D. A.
    Vieira, Marcelo A. C.
    Foi, Alessandro
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2018, 29 (06)
  • [5] X-ray phase-contrast imaging: from pre-clinical applications towards clinics
    Bravin, Alberto
    Coan, Paola
    Suortti, Pekka
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2013, 58 (01) : R1 - R35
  • [6] Inpainting approaches to fill in detector gaps in phase contrast computed tomography
    Brun, F.
    Delogu, P.
    Longo, R.
    Dreossi, D.
    Rigon, L.
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2018, 29 (01)
  • [7] Brun F, 2017, ADV STRUCT CHEM IMAG, V3, DOI 10.1186/s40679-016-0036-8
  • [8] Chukalina M.V., 2019, B RUSSIAN ACAD SCI P, V83, P19
  • [9] Computing segmentations directly from x-ray projection data via parametric deformable curves
    Dahl, Vedrana Andersen
    Dahl, Anders Bjorholm
    Hansen, Per Christian
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2018, 29 (01)
  • [10] GILBERT P, 1972, J THEOR BIOL, V36, P105, DOI 10.1016/0022-5193(72)90180-4