Name: Reconstruction technology
Brand: Philips
SKU: HCNCTD449
Availability: InStock

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Features

Industry-leading low-contrast resolution: Industry-leading low-contrast resolution

IMR provides significant improvements in low contrast detectability, giving you confidence through enhanced visualization of fine detail and improved accuracy in detecting small, subtle structures. This outstanding improvement helps strengthen the position of CT as the backbone of radiology.
Knowledge-based iterative reconstruction technique: Lower dose with higher image quality

You can achieve 60 - 80% lower dose, and at the same time, improve low-contrast detectability by 43 - 80% and lower image noise by 70 - 83%, relative to standard (FBP) reconstruction.*
Virtually noise-free images: Virtually noise-free images

Noise and artifacts limit visualization of critical structural information. IMR breaks the strong linkage between noise and dose, allowing for virtually noise-free** images through 73% to 90% noise reduction, helping reveal information previously hidden in noise.
First knowledge-based IR for Cardiac CTA: First knowledge-based IR for Cardiac CTA

IMR Platinum is the first knowledge-based solution to overcome the motion sensitivity associated with traditional model-based solutions. This allows it to be used in highly advanced acquisitions, such as cardiac CTA.

* In clinical practice, the use of IMR may reduce CT patient dose depending on the clinical task, patient size, anatomical location, and clinical practice. A consultation with a radiologist and a physicist should be made to determine the appropriate dose to obtain diagnostic image quality for the particular clinical task. Low-contrast detectability and noise were assessed using Reference Body Protocol comparing IMR to FBP; measured on 0.8 mm slices, tested on the MITA CT IQ Phantom (CCT183, The Phantom Laboratory), using human observers.
** Image noise as defined by IEC standard 61223-3-5. Image noise was assessed using reference body protocol, on a phantom. Data on file.

Iterative Model Reconstruction