PixelPrint – Precision in Every Pixel!

By utilizing state-of-the-art 3D printing techniques, PixelPrint allows for fabrication of highly accurate, lifelike computed tomography (CT) phantoms that replicate human tissue's intricate textures and densities. These phantoms serve as essential tools in the development, validation, and calibration of computed tomography equipment as well as in the education of next generation medical professionals. Our primary goals include expediting the transformation of novel CT technologies from theoretical concepts to practical applications using PixelPrint phantoms, and further developing the PixelPrint technology to broaden its applicability in CT imaging. PixelPrint phantoms extend beyond the lungs and are available for various other anatomical regions. Moreover, we are committed to making PixelPrint technology available to the broader scientific and medical communities and look forward to collaborating.

This figure illustrates examples of PixelPrint phantoms representing a variety of different disease states in axial CT images. They include Interstitial Pneumonia (row 1), Pulmonary Edema (row 2), and Cystic Fibrosis (row 3). Original patient images are shown in column 1 while corresponding PixelPrint phantom images are shown in column 2 and are remarkably similar to patient images. Multiple zoomed-in images are shown in column 3 with the patient image on the left and the phantom images on the right. All structures in patient images are replicated in phantom images with the same quantitative values. 

For more information, inquiries, sales, or collaboration opportunities, please contact Peter Noël.

PixelPrint References

• Mei, Kai, et al. "Three‐dimensional printing of patient‐specific lung phantoms for CT imaging: emulating lung tissue with accurate attenuation profiles and textures." Medical Physics 49.2 (2022): 825-835.
• Shapira, Nadav, et al. "PixelPrint: three-dimensional printing of realistic patient-specific lung phantoms for CT imaging." SPIE Medical imaging (2022): Vol. 12031. 
• Mei, Kai, et al. "PixelPrint: three-dimensional printing of patient-specific soft tissue and bone phantoms for CT." 7th International Conference on Image Formation in X-Ray Computed Tomography. (2022): Vol. 12304.
• Shapira, Nadav, et al. "Three-dimensional printing of patient-specific computed tomography lung phantoms: a reader study." PNAS Nexus 2.3 (2023): pgad026.
• Reynolds, Tess, et al. "Revealing pelvic structures in the presence of metal hip prostheses via non-circular CBCT orbits." SPIE Medical Imaging (2023): Vol. 12466. 
• Heck, Lisa, et al. "First-generation clinical dual-source photon-counting CT: quantitative and ultra-high-resolution spectral imaging." SPIE Medical Imaging (2023): Vol. 12463.
• Hsieh, Scott S., et al. "A dense search challenge phantom fabricated with pixel-based 3D printing for precise detectability assessment." SPIE Medical Imaging (2023): Vol. 12463.
• Mei, Kai, et al. "PixelPrint: a collection of three-dimensional printed CT phantoms of different respiratory diseases." SPIE Medical Imaging (2023): Vol. 12463. 
• Mei, Kai, et al. "Design and fabrication of 3D-printed patient-specific soft tissue and bone phantoms for CT imaging." Scientific Reports (2023): 17495.
• Im, Jessica Y., et al. "Lifelike PixelPrint phantoms for assessing clinical image quality and dose reduction capabilities of a deep learning CT reconstruction algorithm." SPIE Medical Imaging (2024): Vol. 12925.
• Pasyar, Pouyan, et al. "PixelPrint: generating patient-specific phantoms for spectral CT using dual filament 3D printing." SPIE Medical Imaging (2024): Vol. 12925.
• Shunhavanich, Picha, et al. "3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment." Medical Physics 51.5 (2024): 3265-3274.
• Im, Jessica Y., et al. "Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm." Physics in Medicine and Biology (2024).