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- Redefining computed tomography

Redefining computed tomography
With photon-counting computed tomography (CT)1, Siemens Healthineers developed a radically new technology for clinical routine.
Precise images thanks to photon-counting
Cardiology
Oncology
Pulmonology
Patients benefit from precise, noninvasive diagnosis in cardiology, oncology, and pulmonology – for example in lung follow-up checks for COVID-19 – at reduced radiation dose and lower doses of contrast media.
Podcast episode
Listen to learn about the limitations of traditional CT scanners and how modern scanners have overcome them. You’ll also hear about photon-counting and the impact it has on image quality. Additionally, you’ll find out the role that artificial intelligence can play in sorting and analyzing the large amount of data that modern CT scanners produce.
Stamina and farsightedness
Vision
Perseverance
Team spirit
It took vision, perseverance, and almost 20 years of research and engineering to develop the new technology. Here is why – and how the team did it.
How does CT work?
Tube
Detector
Rotation
Although today not all CT systems are created equal, their basic functionality remains the same: one (or two) X-ray source(s) and detector(s) rotate around the patient, with the detector collecting the X-ray signals that pass through the patient’s anatomy.
The history of CT at Siemens Healthineers
Spiral
Multislice
Dual Soucre
Since its invention by Sir Godfrey Hounsfield in London in 1971, many major milestones in the development of CT technology emerged from Siemens Healthineers, such as spiral CT and dual source CT. And they will certainly not be the last revolutionary inventions in the ongoing history of CT.
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1 The products/features (mentioned herein) are not commercially available in all countries. Their future availability cannot be guaranteed.
- The statements by Siemens Healthineers customers described herein are based on results that were achieved in the customer’s unique setting. Since there is no “typical” hospital and many variables exist (e.g., hospital size, case mix, level of IT adoption) there can be no guarantee that other customers will achieve the same results.