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Basic IMR testing, considerations and image quality trends

White Paper
Philips CT Clinical Science Philips Healthcare • USA

Philips Iterative Model Reconstruction (IMR)

Philips Iterative Model Reconstruction (IMR) has been developed to lower the image noise‡ in CT images. IMR is a software application used to reconstruct images from a CT scanner with lower noise than can typically be attained with Filtered Back Projection (FBP). This feature can be used by radiologists as an alternative method to reconstruct CT raw data, instead of traditional FBP. The information in this paper describes the testing conducted in the development and testing of IMR, and how the results relate to the expected image quality performance.

‡ Image noise as defined by IEC standard 61223-3-5. Image noise was assessed using reference body protocol, on a phantom. Data on file.

This paper is organized as follows:
  • Key performance metrics - describes how the user can reconstruct and demonstrate, on their own, some of the key performance metrics of IMR
  • Basic testing – allows the user to understand some key trends in how IMR reduces image noise, while maintaining or improving spatial resolution
  • Image quality trends – identifies ways in which the noise behavior of IMR is different from that seen with FBP, allowing the user to better understand how clinical scans can be modified to take advantage of IMR’s noise reduction capability
  • Special considerations – Identifies special considerations in the way that IMR may make inherent image quality artifacts more apparent once the image noise has been reduced



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White Paper
iCT, Ingenuity CT
abdomen, artifacts, Body, brain, chest, contrast, dose, facial bones, FBP reconstruction, Head, high resolution, iDose4, image quality, IMR, iterative model reconstruction, Neuro, phantom, sinus, Thorax
 

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