
GE Healthcare has acquired Swedish startup Prismatic Sensors, which specializes in the development of photon-counting detectors for CT scanners and whose CEO is Mats Danielsson, professor in physics of medical imaging in Stockholm.
GE said photon-counting CT technology can create a new standard of care in oncology, cardiology, neurology, and other clinical areas by visualizing the minute details of organ structures, characterizing tissues better, and more accurately determining material density, while also lowering radiation dose.
Prismatic Sensors has patented a method to position silicon sensors "edge on" so the detector is deep enough to absorb very-high-energy photons and fast enough to count hundreds of millions of CT photons per second. Silicon-based detectors enable superior spectral resolution without compromising on count rate or spatial resolution, Prismatic said.
GE expects to complete the Prismatic Sensors acquisition by January 2021. Financial terms of the transaction were not disclosed.
















![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&fit=crop&h=112&q=70&w=112)



