Direkt zum Inhalt
CT Lab HX
Features
  • Compact benchtop design
  • 130 kV, 39 W high-power X-ray source
  • Large field of view (max. 200 mm diameter)
  • High-resolution (max. 2.2 μm voxel resolution)
  • High-speed (max. 18 seconds/scan)
  • Easy-to-use software

Versatile X-ray Micro-Ct Scanner

High-performance benchtop

CT Lab HX

Rigaku CT Lab HX is a high-performance benchtop X-ray micro-CT system with the most powerful X-ray source in its class (130 kV, 39 W). The CT Lab HX has the advantage of a small footprint with low running costs.

Versatile: Both the sample stage and detector positions are selectable. This flexible geometry eliminates wasted space and accommodates a wide range of settings, from a maximum 200 mm field of view (FOV) to the best voxel resolution 2.2 µm in a benchtop system.

The powerful X-ray source covers a wide variety of applications, from polymer and bones to electronics and metals, and enables fast data collection at 18 seconds per scan.

Live mode and in-situ imaging: Observe real-time structural changes in-situ with 2D live mode image collection or high-speed CT scans. These features are effective for observing flow and diffusion of liquid or structural change caused by environmental changes.

Specifications
Product name CT Lab HX
Benefit High-performance benchtop X-ray micro-CT
Technology X-ray computed tomography
X-ray generator 39 W sealed microsource
Tube voltage 30 to 130 kV
Tube current up to 300 μA
Target W
Detector Flat-panel
Field of view Maximum 200 mm
Resolution Maximum 2.2 μm

Webinars - X-ray Computed Tomography for Materials Science

Angela Criswell, Aya Takase
A live demonstration of X-ray Computed Tomography (CT) data analysis using ImageJ (an open platform for scientific image analysis). You don’t need any commercial software licenses to enjoy this workshop. We will review the basic operations of ImageJ and analyze CT images. All data sets used in the demonstration are available to the audience. We encourage the participants to download the Fiji distribution of ImageJ and demo data sets and follow the process with us. We will send registrants download links to Fiji installer and datasets before the workshop.
Angela Criswell
In this webinar, we discuss sample preparation techniques for life science samples. These samples typically require preservation to ensure that ‘as lifelike as possible’ CT data can be collected. Additionally, these types of samples typically have low density contrast and thus benefit from staining. Different techniques are discussed, and we show examples of X-ray CT data for life science samples.
Angela Criswell | Co-Presenter: Tim Bradow
In this webinar, we will discuss important factors to consider when using X-ray CT methods to inspect batteries. We will also examine data analysis techniques to extract meaningful insight into battery structure and function.

X-ray CT Publications


Our first CT project

Morio ONOE, Jing Wen TSAO and Hiroaki YAMADA, Hiroshi NAKAMURA, Jin KOGURE and Hiromi KAWAMURA, M. Y. (1984). COMPUTED TOMOGRAPHY FOR MEASURING THE ANNUAL RINGS OF A LIVE TREE. Nuclear Instruments and Methods in Physics Research, 221, 213-220. https://www.sciencedirect.com/science/article/pii/0167508784902023 

  1. Joseph P. Neilly, Leilei Yin, Sarah-Ellen Leonard, Paul J.A. Kenis, Gerald D. Danzer, Ashtamurthy S. Pawate (2019) Quantitative Measures of Crystalline Fenofibrate in Amorphous Solid Dispersion Formulations by X-Ray Microscopy, Journal of Pharmaceutical Sciences, 109(10), 3078-3085 https://www.sciencedirect.com/science/article/pii/S0022354920303683
  2. Carolina Oliver-Urrutia, Raúl Rosales Ibañez, Miriam V. Flores-Merino, Lucy Vojtova, Jakub Salplachta, Ladislav Čelko, Jozef Kaiser, and Edgar B. Montufar (2021). Lyophilized Polyvinylpyrrolidone Hydrogel for Culture of Human Oral Mucosa Stem Cells. Materials 14, 227. https://www.mdpi.com/1996-1944/14/1/227/htm
  3. Tomáš Sedlačík, Takayuki Nonoyama, Honglei Guo, Ryuji Kiyama, Tasuku Nakajima, Yoshihiro Takeda, Takayuki Kurokawa, and Jian Ping Gong (2020). Preparation of Tough Double- and Triple-Network Supermacroporous Hydrogels through Repeated Cryogelation. Chem. Mater. Published online18 September 2020. https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.0c02911
  4. Nanako Sakata, Yoshihiro Takeda, Masaru Kotera, Yasuhito Suzuki, and Akikazu Matsumoto. (2020). Interfacial Structure Control and Three-Dimensional X-ray Imaging of an Epoxy Monolith Bonding System with Surface Modification. Langmuir, 36, 37, 10923–10932. https://pubs.acs.org/doi/10.1021/acs.langmuir.0c01481
  5. Kenji Ohta , Tatsuya Wakamatsu, Manabu Kodama , Katsuyuki Kawamura, and Shuichiro Hirai. Laboratory-based x-ray computed tomography for 3D imaging of samples in a diamond anvil cell in situ at high pressures. Rev. Sci. 91, 091101. https://aip.scitation.org/doi/pdf/10.1063/5.0014486
  6. Fukami, T., Koide, T., Hisada, H., Inoue, M., Yamamoto, Y., Suzuki, T., & Tomono, K. (2016). Pharmaceutical evaluation of atorvastatin calcium tablets available on the Internet: A preliminary investigation of substandard medicines in Japan. Journal of Drug Delivery Science and Technology, 31, 35-40. https://doi.org/10.1016/j.jddst.2015.11.006 
  7. Kalasova, D., Zikmund, T., Pina, L., Takeda, Y., Horvath, M., Omote, K., & Kaiser, J. (2019). Characterization of a laboratory-based X-ray computed nanotomography system for propagation-based method of phase contrast imaging. IEEE Transactions on Instrumentation and Measurement, PP(c), 1-1. https://doi.org/10.1109/tim.2019.2910338 
  8. Kunishima, N., Takeda, Y., Hirose, R., Kalasová, D., Šalplachta, J., & Omote, K. (2020). Visualization of internal 3D structure of small live seed on germination by laboratory-based X-ray microscopy with phase contrast computed tomography. Plant Methods, 16(1), 1-10. https://doi.org/10.1186/s13007-020-0557-y 
  9. Zhang, S., Byrnes, A. P., Jankovic, J., & Neilly, J. (2019). Management, Analysis, and Simulation of Micrographs with Cloud Computing. Microscopy Today, 27(2), 26-33. https://doi.org/10.1017/s1551929519000026 
  10. Kalasová, D., Zikmund, T., Pína, L., Horváth, M., & Kaiser, J. (2016). Phase contrast tomographic imaging of polymer composites. 2020, 2020. http://ctlab.ceitec.cz/files/252/165.pdf 
  11. Kalasova, D., Pavlinakova, V., Zikmund, T., Vojtova, L., & Kaiser, J. (2018). Correlation of X-ray Computed Nanotomography and Scanning Electron Microscopy Imaging of Collagen Scaffolds. Microscopy and Microanalysis, 24(S2), 104-105. https://doi.org/10.1017/s1431927618012904 
  12. Hisada, K., Matsuoka, M., Tabata, I., Hirogaki, K., & Hori, T. (2013). Two-step radical grafting onto polypropylene fiber initiated by active species prepared through the irradiation of electron beam. Journal of Photopolymer Science and Technology, 26(2), 277-282. https://doi.org/10.2494/photopolymer.26.277 
  13. Sekita, A., Matsugaki, A., & Nakano, T. (2017). Disruption of collagen/apatite alignment impairs bone mechanical function in osteoblastic metastasis induced by prostate cancer. Bone, 97, 83-93. https://doi.org/10.1016/j.bone.2017.01.004 
  14. Nanako Sakata, Yoshihiro Takeda, Masaru Kotera, Yasuhito Suzuki, and A. M. (2020). Non‐destructive 3D X‐ray Imaging of Internal and Interfacial Structure of Epoxy Monolith and Strength Control by Surface Modification for the Monolith Bonding System. Langmuir. https://pubs.acs.org/doi/abs/10.1021/acs.langmuir.0c01481 
  15. Tomáš Sedlačík, Takayuki Nonoyama, Honglei Guo, Tasuku Nakajima, Yoshihiro Takeda, Takayuki Kurokawa, J. P. G. (2020). Tough Double- and Triple- Network Supermacroporous Hydrogels through Repeated Cryogelation. ACS Publications. https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.0c02911 
  16. Kakio, T., Yoshida, N., Macha, S., Moriguchi, K., Hiroshima, T., Ikeda, Y., Kimura, K. (2017). Classification and visualization of physical and chemical properties of falsified medicines with handheld Raman spectroscopy and X-Ray computed tomography. American Journal of Tropical Medicine and Hygiene, 97(3), 684-689. https://doi.org/10.4269/ajtmh.16-0971 
  17. Takase, A., McNulty, T., & Fitzgibbons, T. (2018). Foam Porosity Calculation by X-Ray Computed Tomography and Errors Caused by Insufficient Resolution. Microscopy and Microanalysis, 24(S2), 546-547. https://doi.org/10.1017/s1431927618014927 
  18. Omote, K., Iwata, T., Takeda, Y., & Ferrara, J. D. (2017). Investigation for fuel-cell structures with multi-scale X-ray analysis. Rigaku Journal, 33(2), 8-13. https://www.semanticscholar.org/paper/Investigation-for-fuel-cell-structures-with-X-ray-Omote-Iwata/78e57af8fa13252533eabb7d5e5a32ceadac9eaa?p2df 
  19. Watanabe, M., Takeda, Y., Maruyama, T., Ikeda, J., Kawai, M., & Mitsumata, T. (2019). Chain structure in a cross-linked polyurethane magnetic elastomer under a magnetic field. International Journal of Molecular Sciences, 20(12). https://doi.org/10.3390/ijms20122879 
  20. Kunishima, N., Takeda, Y., Hirose, R., Kalasová, D., Šalplachta, J., & Omote, K. (2020). Visualization of internal 3D structure of small live seed on germination by laboratory-based X-ray microscopy with phase contrast computed tomography. Plant Methods, 16(1), 1-10. https://doi.org/10.1186/s13007-020-0557-y 
  21. Kalasova, D., Zikmund, T., Pina, L., Takeda, Y., Horvath, M., Omote, K., & Kaiser, J. (2020). Characterization of a laboratory-based x-ray computed nanotomography system for propagation-based method of phase contrast imaging. IEEE Transactions on Instrumentation and Measurement, 69(4), 1170-1178. https://doi.org/10.1109/TIM.2019.2910338 
  22. Akitomo, F., Sasabe, T., Yoshida, T., Naito, H., Kawamura, K., & Hirai, S. (2019). Investigation of effects of high temperature and pressure on a polymer electrolyte fuel cell with polarization analysis and X-ray imaging of liquid water. Journal of Power Sources, 431(February), 205-209. https://doi.org/10.1016/j.jpowsour.2019.04.115 
  23. Watanabe, M., Takeda, Y., Maruyama, T., Ikeda, J., Kawai, M., & Mitsumata, T. (2019). Chain structure in a cross-linked polyurethane magnetic elastomer under a magnetic field. International Journal of Molecular Sciences, 20(12). https://doi.org/10.3390/ijms20122879 
  24. Kalasová, D., Zikmund, T., Mancini, L., Jaroš, J., Tesařová, M., Kaucká, M., Kaiser, J. (2016). Industrial Tomography System for Answering Biological Issues: Development of the Mouse Embryo Face. 6th Conference on Industrial Computed Tomography (ICT 2016), (iCT), 1-9. https://www.ndt.net/article/ctc2016/papers/ICT2016_paper_id37.pdf 
  25. Tanaka, K., Yamada, T., Moriito, K., & Katayama, T. (2016). The effect of molding pressure on the mechanical properties of CFRTP using paper-type intermediate material. High Performance and Optimum Design of Structures and Materials II, 1(Hpsm), 307-315. https://doi.org/10.2495/hpsm160281 
  26. Watanabe, M., Ikeda, J., Takeda, Y., Kawai, M., & Mitsumata, T. (2018). Effect of Sonication Time on Magnetorheological Effect for Monomodal Magnetic Elastomers. Gels, 4(2), 49. https://doi.org/10.3390/gels4020049 
  27. Fukami, T., Koide, T., Hisada, H., Inoue, M., Yamamoto, Y., Suzuki, T., & Tomono, K. (2016). Pharmaceutical evaluation of atorvastatin calcium tablets available on the Internet: A preliminary investigation of substandard medicines in Japan. Journal of Drug Delivery Science and Technology, 31, 35-40. https://doi.org/10.1016/j.jddst.2015.11.006 
  28. Eiichi Yamamoto, Yoshihiro Takeda, Daisuke Ando, Tatsuo Koide, Yuta Amano, Shingo Miyazaki, Tamaki Miyazaki, Ken-ichi Izutsu, Hideko Kanazawa, and Yukihiro Goda. (2021). Discrimination of ranitidine hydrochloride crystals using X-ray micro-computed tomography for the evaluation of three-dimensional spatial distribution in solid dosage forms. Int. J. Pharm. Available online 28 June 2021, 120834 https://doi.org/10.1016/j.ijpharm.2021.120834
  29. Naoki Kunishima, Raita Hirose, Yoshihiro Takeda, Koichiro Ito, Kengo Furuichi & Kazuhiko Omote. (2022). Nondestructive cellular-level 3D observation of mouse kidney using laboratory-based X-ray microscopy with paraffin-mediated contrast enhancement. Scientific Reports volume 12, Available online 10 June 2022. https://doi.org/10.1038/s41598-022-13394-9

  1. Aung, W., Jin, Z. H., Furukawa, T., Claron, M., Boturyn, D., Sogawa, C., … Saga, T. (2013). Micro-positron emission tomography/contrast-enhanced computed tomography imaging of orthotopic pancreatic tumor-bearing mice using the αvβ3 integrin tracer 64Cu-labeled cyclam-RAFT-c(-RGDfK-)4. Molecular Imaging, 12(6), 376-387. https://doi.org/10.2310/7290.2013.00054 
  2. Arai, Y., Yamada, A., Ninomiya, T., Kato, T., & Masuda, Y. (2005). Micro-computed tomography newly developed for in vivo small animal imaging. Oral Radiology, 21(1), 14-18. https://doi.org/10.1007/s11282-005-0024-5 
  3. Reedy, C. L. (2020). 3D Documentation and Analysis of Porosity in Deteriorated Historic Brick. Studies in Conservation, 0(0), 1-4. https://doi.org/10.1080/00393630.2020.1752426 
  4. Iikubo, M., Nishioka, T., Okura, S., Kobayashi, K., Sano, T., Katsumata, A., … Sasano, T. (2016). Influence of voxel size and scan field of view on fracture-like artifacts from gutta-percha obturated endodontically treated teeth on cone-beam computed tomography images. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology, 122(5), 631-637. https://doi.org/10.1016/j.oooo.2016.07.014 
  5. Benjamin M. Davis, Glen F. Rall, M. J. S. (2017). HHS Public Access. Physiology & Behavior, 176(1), 139-148. https://doi.org/10.1016/j.physbeh.2017.03.040 
  6. Bolmin, O., Wei, L., Hazel, A. M., Dunn, A. C., Wissa, A., & Alleyne, M. (2019). Latching of the click beetle (Coleoptera: Elateridae) thoracic hinge enabled by the morphology and mechanics of conformal structures. Journal of Experimental Biology, 222(12). https://doi.org/10.1242/jeb.196683 
  7. Kameoka, S., Matsumoto, K., Kai, Y., Yonehara, Y., Arai, Y., & Honda, K. (2010). Establishment of temporomandibular joint puncture technique in rats using in vivo micro-computed tomography (R-mCT®). Dentomaxillofacial Radiology, 39(7), 441-445. https://doi.org/10.1259/dmfr/37174063 

  1. Hagen, C. K., Vittoria, F. A., Morgó, O. R. I., Endrizzi, M., & Olivo, A. (2020). Cycloidal Computed Tomography. Physical Review Applied, 14(1), 1. https://doi.org/10.1103/PhysRevApplied.14.014069 
  2. Diemoz, P. C., Hagen, C. K., Endrizzi, M., Minuti, M., Bellazzini, R., Urbani, L., … Olivo, A. (2017). Single-Shot X-Ray Phase-Contrast Computed Tomography with Nonmicrofocal Laboratory Sources. Physical Review Applied, 7(4), 1-6. https://doi.org/10.1103/PhysRevApplied.7.044029 
  3. Hagen, C. K., Endrizzi, M., Diemoz, P. C., & Olivo, A. (2016). Reverse projection retrieval in edge illumination x-ray phase contrast computed tomography. Journal of Physics D: Applied Physics, 49(25). https://doi.org/10.1088/0022-3727/49/25/255501 
  4. Zamir, A., Endrizzi, M., Hagen, C. K., Vittoria, F. A., Urbani, L., De Coppi, P., & Olivo, A. (2016). Robust phase retrieval for high resolution edge illumination x-ray phase-contrast computed tomography in non-ideal environments. Scientific Reports, 6(August), 1-9. https://doi.org/10.1038/srep31197