1. Medical Imaging
  2. Radiology
  3. CT scanner
  4. MinFound Medical Systems

CT scanner ScintCare CT16
for whole-body tomography16-slice

CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice
CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice
CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice - image - 2
CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice - image - 3
CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice - image - 4
CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice - image - 5
CT scanner - ScintCare CT16 - MinFound Medical Systems - for whole-body tomography / 16-slice - image - 6
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Characteristics

Type of system
CT scanner
Application
for whole-body tomography
Number of slices
16-slice
Rotation time (s)

0.5 s

Generator power (kW)

50,000 W

Description

ScintCare CT16 features precision and stability. With the powerful Scinticare detector, reliable key components, and advanced software platform, ScintCare CT16 is built to provide decent images while maintaining low radiation dose and boost efficiency and confidence in daily imaging diagnosis. Specifications: Power: 50 kW Gantry Bore: 70 cm Scan Speed: 67mm/s Highlights: 1. 5.3 M tube powers a greater patient throughput up to 150 patients per day. 2. 0.6 mm minimum slice thickness enables the obtaining of more precise organ images. 3. The ScintiStar® Detector guarantees sufficient sampling per rotation with low afterglow and reduced artifacts. 4. NanoDose Iterative (NDI) and intelligent mA (imA) algorithms enable lower dose while preserving image quality. 5. 1024 x 1024 Mega-pixel matrix fully displays details of lesions. 6. AI-empowered workflow provides easy and comfortable operation. 7. Robust hardware allows stable running. NDI NanoDose Iteration Algorithm (NDI) is an innovative iterative technique for image reconstruction that takes full advantage of deep learning in anatomical structure in image space as well as model-driven iteration involving tube and detector in projection space, with the aim to generate sharp and high-resolution images at the lowest possible dose.

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Exhibitions

Meet this supplier at the following exhibition(s):

ArabHealth 2025
ArabHealth 2025

27-30 Jan 2025 Dubai (United Arab Emirates) Hall S2 - Stand E82

  • More information
    ArabLab 2025
    ArabLab 2025

    23-25 Sep 2025 dubai (United Arab Emirates)

  • More information
    *Prices are pre-tax. They exclude delivery charges and customs duties and do not include additional charges for installation or activation options. Prices are indicative only and may vary by country, with changes to the cost of raw materials and exchange rates.