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Photon Counting CT

Unlock the full potential of PCCT.

Introducing our next-generation Canon photon-counting CT scanner that combines proprietary detector technology with AI-driven Deep Learning Reconstruction to deliver exceptional image quality.

Fundamentaily different than a conventional CT, it delivers Ultra-High Resolution and advanced Spectral images and further dose reduction, providing new clinical value.

It’s time to advance to the next phase of Canon CT innovation.

*Ultimion is not available for sale outside of Japan.

Since its inception in 1971, the dramatic evolution of Computed Tomography (CT) has led to the steady growth of CT’s role in patient care.

 

Canon has pioneered many of the technological innovations defining the clinical expansion of CT, such as Area Detectors, Ultra-High Resolution, and Deep Learning Reconstruction. In partnership with Redlen Technologies Inc. (Redlen), a Canon group company, the global leader in photon counting detector design and manufacturing, Canon is currently developing a Photon Counting CT (PCCT) with the potential to improve visualization of small structures and enhance tissue characterization.

 

Our vision is to use Redlen’s state-of-the-art Photon Counting CT technology empowered by Canon’s leading advancements in system, software, and image reconstruction to improve the quality of medical diagnosis for all patients worldwide.

CANON'S PHOTON COUNTING CT

Canon’s PCCT detector is uniquely constructed using Cadmium Zinc Telluride (CZT). The addition of Zinc to Cadmium Telluride increases the detector’s ability to effectively capture photons, for greater dose efficiency. In addition, Canon’s exclusive compact read out circuitry is designed to maximize the active area of the detector to achieve the highest geometric dose efficiency. With an optimized pixel size, fast read out, and sophisticated modelling algorithms, Canon’s CZT detector readily combats challenges such as pulse pileup and charge sharing to yield low noise, high-resolution images.

WHAT IS PHOTON COUNTING CT?

Photon counting CT uses a semiconductor material to directly convert each incident photon into an electric signal, which is then quickly read out by detector circuity to effectively “count” each photon individually. When an incident photon strikes the detector, it creates a charge cloud in the detector material proportional to the energy of incident photon. Based on their measured energy, the counted photons are sorted into energy bins that can be utilized by advanced reconstruction techniques to generate optimal image quality and spectral information.

WHAT IS THE MAIN DIFFERENCE OF PHOTON COUNTING FROM CONVENTIONAL CT?

A PCCT measures each photon and its energy directly, whereas with a conventional Energy Integrating Detector (EID) the incident photons are not directly converted to signal. Rather, the absorbed energy of the photons is first converted to light by a scintillator, then that light is converted to an electrical signal by a photodiode. An EID’s output depends on the combined energy of the incident photons. Higher energy photons generate more light than lower energy photons, and thus contribute more heavily towards the EID’s output electrical signal.

BENEFITS OF CANON’S PCCT: IMAGE QUALITY

The key to achieving the best image quality PCCT can offer is reconstruction. Canon’s long history of advances in reconstruction that have shattered the boundaries of image quality performance have led the way for Canon to optimize PCCT image quality for all patient shapes and sizes.

For more optimal dose efficiency, detectors should have as much active area capturing photons as possible. In conventional EIDs, light in one detector pixel can scatter into a neighboring pixel, a phenomenon called optical crosstalk that reduces spatial resolution. Because of this, EIDs require a reflector of finite thickness between the scintillator pixels to prevent crosstalk. However, the presence of this reflector reduces the active area of the detector and, thus, its dose efficiency, especially for small-sized detector pixels. Because PCCT doesn’t use a scintillator, there is no need for reflective material between detector pixels. This greatly improves the dose efficiency of the detector, allowing for smaller detector pixel sizes without dose penalty.

 

PCCT also overcomes a major disadvantage of EID: electronic noise. An EID’s electronic noise is unavoidably combined with true signal into the detector output. When the number of photons is low, electronic noise becomes dominant, degrading image quality. With PCCT, electronic noise from the detector registers below the threshold of lowest energy bin and is thus discarded. In this way, PCCT effectively eliminates electronic noise, which improves image quality.

BENEFITS OF CANON’S PCCT: SPECTRAL

PCCT enables Spectral Imaging with every scan for routine material decomposition. Canon’s exclusive advances in Spectral reconstruction have given Canon unique insight into minimizing noise and maximizing spectral information from PCCT. Because the thresholds for the energy bins are configurable, PCCT can also allow for imaging that targets specific K-edge energies, from common contrast agents, such as iodine and gadolinium, to novel nanoparticles such as gold.

BENEFITS OF CANON'S PCCT: ULTRA-HIGH RESOLUTION (UHR)

PCCT detectors permit the use of small detector pixels. In standard applications, these pixels can be combined to yield improved spatial resolution relative to conventional CT without noise or dose penalty. For applications where increased spatial resolution adds clinical value, these pixels can be read out individually for Ultra-High Spatial Resolution. Canon launched the Aquilion Precision Ultra-High Resolution (UHR) CT system in 2017 and has now obtained over half a decade of expertise in reconstruction and workflow optimization for UHR as well as achieved advances in tube design, table positioning, and gantry vibration to make the most effective use of UHR-CT. With these advances, Canon is posed to lead the way on UHR PCCT for maximum clinical utility and optimal workflow in a busy clinical environment.

THE ADVANTAGE OF REDLEN, A CANON GROUP COMPANY

Redlen has been developing photon counting detector manufacturing technology for over twenty years and is today a leading global supplier of photon counting imaging detectors. In addition to medical imaging, Redlen CZT technology is currently used globally in security scanning, non-destructive industrial scanning, and aerospace applications.

Redlen’s extensive manufacturing experience has resulted in a fully vertically integrated manufacturing system that spans CZT material growth, wafer processing, sensor fabrication, imaging module design, module assembly, module production testing and finally CZT material recycling, all under one roof. As a result, Canon can realize the stable production of the highly precise photon counting CT detectors. Combined with Canon’s sophisticated CT manufacturing capabilities for gantry, tube, and table, the result is a revolutionary step forward in PCCT.

We're currently accumulating knowledge regarding both the technical and clinical benefits of our photon counting CT system.

Scientific papers

  1. H. Kuno, T. Hiyama, T. Sasaki et al. Imaging-detected extranodal extension in head and neck cancer: clinical implications, diagnostic criteria, and the potential of photon-counting detector CT. Jpn J Radiol. 2025 Oct 16. doi: 10.1007/s11604-025-01894-3. Online ahead of print. PMID : 41099987.
  2. T. Sasaki, H. Kuno, K. Nomura, Y. Muramatsu, K. Aokage, J. Samejima, T. Taki, E. Goto, M. Wakabayashi, H. Furuya, H. Taguchi, T. Kobayashi. CZT-based photon-counting-detector CT with deep-learning reconstruction: image quality and diagnostic confidence for lung tumor assessment. Jpn J Radiol. 2025 Mar 7. doi: 10.1007/s11604-025-01759-9. Online ahead of print. PMID: 40053285.
  3. Lee D, Zhan X, Tai WY, Zbijewski W, Taguchi K. Improving model-data mismatch for photon-counting detector model using global and local model parameters. Med Phys. 2023 Dec 8. doi: 10.1002/mp.16883. Epub ahead of print. PMID: 38064641.
  4. Zhan X, Zhang R, Niu X, Hein I, Budden B, Wu S, Markov N, Clarke C, Qiang Y, Taguchi H, Nomura K, Muramatsu Y, Yu Z, Kobayashi T, Thompson R, Miyazaki H, Nakai H. Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies. Phys Med Biol. 2023 Aug 14;68(17). doi: 10.1088/1361-6560/acebb3. PMID: 37506710


Conference presentations

  1. F. Tatsugami et al. Impact of Photon-Counting Detector CT on Visualization of the Adamkiewicz Artery Using Super-High-Resolution Mode with Deep Learning Reconstruction: A First Experience. RSNA 2025
  2. T. Higaki et al. Maximizing Image Quality Through the Synergy of High-Resolution Photon-Counting Detector CT and Deep Learning Reconstruction: A Coronary Phantom Study. RSNA 2025
  3. T. Sasaki et al. Quantitative Analysis of Pulmonary Emphysema Using Electron Density Images from Photon-Counting Detector CT: Correlation with Pulmonary Function Tests. RSNA 2025
  4. Kai Mei et al. Photon-Counting Detector CT and Deep Learning Reconstruction in Lung Lesion Assessment. RSNA 2025
  5. Leening P. Liu et al. Assessing the Utility of Photon-Counting CT in Obese Patients. RSNA 2025
  6. Fong Chi Ho et al. Task-specific Evaluation of Photon-Counting CT Using a 3D-Printed Anthropomorphic Lung Phantom with COPD Pathology. RSNA 2025
  7. Yuxin Sun et al. Use of Dark Attenuation Oral Contrast Agent Improves Delineation of Thin Structures at Ultra-High Resolution and Photon-Counting Detector CT. RSNA 2025
  8. Gisell Ruiz. Association between Detectability Index and Volumetric Accuracy in Low-Dose Energy-Integrating and Photon-Counting CT. RSNA 2025
  9. Gisell Ruiz et al. Evaluation of Reconstruction Kernels and Resolution Techniques for Volumetric Accuracy of Ground-Glass Opacity Nodules in Low-Dose Photon-Counting CT. RSNA 2025
  10. W. Y. Tai et al. Impact of Scatter on Phantom-based Water Pathlength Calibration in Photon-Counting CT. 2025 IEEE NPSS
  11. Leening P. Liu et al. Assessing the Utility of Photon-Counting CT in Obese Patients. 2025 IEEE MIC
  12. Y. Nakamura et al. Utility of CZT-based photon counting detector CT for an abdominal thin-slice non-contrast CT images in comparison with energy integrating detector CT. ECR 2025
  13. Y. Nakamura et al. Utility of virtual non-contrast images derived from CZT-based photon counting detector CT in comparison with true non-contrast images. ECR 2025
  14. H. Kuno et al. Imaging-detected Extranodal Extension in Head and Neck Cancer: Clinical Implications and Diagnostic Criteria in the Era of High-Resolution Imaging including Photon-Counting Detector CT. RSNA 2024
  15. T. Sasaki et al. CZT-based Photon-Counting-Detector CT with Deep-Learning Reconstruction: Image Quality and Diagnostic Confidence for Lung Tumor Assessment. RSNA 2024
  16. K. Nomura et al. Sharpness Evaluation of Chest Multi Planar Reconstruction Images with Normal and Super High-resolution Mode of CZT-Based Photon-counting Detector CT. RSNA 2024
  17. A. Pourmorteza et al. Dose-Efficient Characterization of Coronary Artery Plaques with a Prototype CdZnTe-Based Photon-Counting CT Scanner. SPIE 2024
  18. A. Pourmorteza et al. Iodine Quantification with a CdZnTe Clinical Prototype Photon-Counting Scanner at Reduced Radiation Dose: Initial Cardiac Phantom Results, ECR 2024
  19. K. Mei et al. Ultra-low-dose photon-counting CT: Assessing radiomic features with a patient-based lung phantom, ECR 2024
  20. S. Mochinaga et al. First Results of Electron Density Quantification with CZT-based Photon Counting Detector CT, ECR 2024
  21. W. Fukumoto et al. Comparison of newly developed CZT-based Photon Counting Detector CT (PCD-CT) and Ultra-High-Resolution CT (U-HRCT) for measuring airway dimensions: A phantom study. ECR 2024
  22. K. Yokomachi et al. Physical characteristics in slice direction using a newly developed CZT-based Photon-Counting Detector CT. ECR 2024
  23. Y. Nakamura et al. Accuracy of CT values on virtual monochromatic images of CZT-based Photon Counting Detector CT: comparison with dual-energy CT using energy integrating detector in a phantom model. ECR 2024
  24. T. Higaki et al. Utility of multi-energy mode of CZT-based Photon Counting Detector CT for coronary CT angiography: A structured phantom study. ECR 2024
  25. D. Lee et al. Advanced Photon-Counting Detector Simulator with a Count-Rate-Dependent Mapping Operator and a Pixel-to-Pixel Variation Generator. IEEE MSS MIC 2023
  26. A. Pourmorteza et al. Dose-efficient Ultra-high-resolution imaging of coronary stents with a CdZnTe-based clinical prototype photon- counting scanner. RSNA 2023
  27. K. L. Boedeker et al. Technical Performance of Super Resolution Deep Learning Reconstruction Algorithm on a Wide Area, Conventional Energy-Integrating Detector vs and a Photon-Counting Computed Tomography System with Conventional Reconstruction Algorithms. RSNA 2023
  28. T. Sasaki et al. CT Imaging of Lung Cancer: Exploring the Clinical Potential of CZT-based Photon Counting Detector CT. RSNA 2023
  29. K. Hirayama et al. Super-high-resolution abdominal imaging using CZT based photon counting CT with deep learning reconstruction: quantitative study and first clinical impression. RSNA 2023
  30. K. Nomura et al. Super-high-resolution chest imaging using CZT-based photon counting CT: performance characterization and first clinical trial. RSNA 2023
  31. S. Mochinaga et al. High z-axis resolution imaging using CZT based photon counting CT: quantitative study and first clinical trial. RSNA 2023
  32. Kei Mei et al. Evaluation of a prototype photon-counting CT for pulmonary imaging using patient-based lung phantoms. RSNA 2023
  33. S. Kondo et al. Visualization of simulated small vessels on photon counting detector CT: comparison with energy integrating CT in a phantom model. RSNA 2023
  34. T. Higaki et al. Improving spatial resolution in coronary CT angiography with photon counting detector CT: A structured phantom study. RSNA 2023
  35. T. Higaki et al. Noise reduction in coronary CT angiography with photon counting detector CT: A structured phantom study. RSNA 2023
  36. F. Tatsugami et al. Coronary Artery Calcium Volume Measurement: A Comparison between Photon-Counting CT and Ultra-High-Resolution CT using a Cardiac CT Calibration Phantom. RSNA 2023
  37. K. Nomura et al. Basic Image Quality Evaluation of New Platform Prototype Photon Counting CT. JRC 2023
  38. X. Zhan et al. Spectral imaging performance evaluation for a prototype full-size photon counting CT system at clinical dose levels. JRC 2023
  39. R. Zhang et al. Quantitative image quality comparison between normal resolution and super high resolution modes of a clinical prototype photon counting CT system. JRC 2023
  40. T. W. Holmes et al. Pediatric head and neck imaging with a CZT-based photon-counting CT scanner: initial image quality evaluation. ECR 2023
  41. K. Nomura et al. Comparison of CT image quality for different sized phantom between prototype full-size photon counting and conventional CT systems: CT number, image noise and artifact. ECR 2023
  42. Edgar Salazar et al. Evaluation of a prototype photon-counting CT for low-dose pulmonary imaging using patient-based lung phantom. ECR 2023
  43. X. Zhan et al. A study of cross-talk effect in pixelated photon counting detectors and impact to system imaging performance. SPIE 2023
  44. Donghyeon Lee et al. Photon-Counting Detector Model Using Local Parameters for Pixel-to-Pixel Variation. SPIE 2023
  45. W. Yang Tai et al. Effects of Bowtie Scatter on Material Decomposition in Photon-Counting CT. SPIE 2023
  46. R. Zhang et al. Quantitative Image Quality Comparison between Photon Counting and Conventional CT Systems: Contrast-to-Noise Ratio. RSNA 2022
  47. K. L. Boedeker et al. Low Contrast Detectability Comparison Between a Prototype Photon Counting Computed Tomography System and Conventional CT system Across a Range of Attenuation Levels. RSNA 2022
  48. Xiaohui Z et al. Quantitative image quality evaluation for a prototype photon counting CT through phantom studies: Noise, Resolution and Quantitative Accuracy. CERN SpecXray 2022
  49. A. Pourmorteza et al. First experience with a clinical prototype CZT-based PCCT scanner: applications in low-dose lung cancer screening. CERN SpecXray 2022
  50. Xiaohui Z et al. Phantom imaging evaluations of a prototype CZT based photon counting system. ECR 2022
  51. K. Nomura et al. Quantitative image quality comparison between a prototype full-size photon counting CT system and conventional CT systems with energy integrating detectors. ECR 2022
  52. T. W. Holmes et al. Low-Dose Lung Cancer Screening with a Novel CZT Photon-Counting CT Prototype: A Phantom Study. ECR 2022
  53. Y Suzuki et al. Physics Performance Evaluation of Prototype Photon Counting CT: Basic Image Quality Evaluation. JRC 2022
  54. K. Nomura et al. Physics Performance Evaluation of Prototype Photon Counting CT: Quantitative Evaluation. JRC 2022
  55. Y. Muramatsu et al. Physics Performance Evaluation of Prototype Photon Counting CT: Large-phantom Evaluation. JRC 2022
  56. Xiaohui Z et al. First results from a prototype full-size photon counting CT system: counting and spectral imaging performance at clinical dose levels. RSNA 2021
  57. K. Nomura et al. Quantitative image quality comparison between photon counting and conventional CT systems: noise, resolution and quantitative accuracy. RSNA 2021