Deep learning "super resolution" versus iterative reconstruction: Phantom-based image quality assessment.

Journal: Journal of applied clinical medical physics
Published Date:

Abstract

BACKGROUND: Deep learning reconstruction (DLR) algorithms have begun replacing iterative reconstruction (IR) in CT. Besides the potential to reduce noise, the application of artificial intelligence can also allow for "super resolution," allowing traditional CT systems to produce images with improved spatial resolution by training against higher-resolution images. This study aims to characterize the image quality produced by a DLR "super resolution" algorithm. PURPOSE: This study compares Canon's Precise IQ Engine (PIQE) Cardiac, a DLR algorithm, with the AIDR Enhanced 3D iterative reconstruction (IR) algorithm using quantitative phantom-based image quality measurements. MATERIALS AND METHODS: Scans of the American College of Radiology (ACR) Gammex 464 image quality phantom with and without a torso-sized elliptical ring were acquired using CTDIvol of 2.6, 15.7, and 32.9 mGy. Each experimental condition was scanned 20 times. Reconstructions used AIDR with a cardiac kernel and PIQE Cardiac with both 512 × 512 and 1024 × 1024 matrices. The task-based modulation transfer function (MTFtask) was calculated for Teflon, acrylic, polyethylene, and air inserts. Contrast-to-noise ratio (CNR) and low-contrast object specific CNR (CNRLO) were calculated for the 25-mm and 6-mm low-contrast disks in module 2 of the phantom. NPS and noise magnitude were calculated from the module's background. RESULTS: Both versions of PIQE showed improvement in MTFtask over AIDR for most frequencies, with PIQE 1024 outperforming PIQE 512. Larger differences were noted at higher contrast levels and with the smaller phantom. NPS curves for PIQE 512 and PIQE 1024 were nearly identical at all doses. AIDR showed a noise magnitude at least 44% higher than PIQE for all scenarios. The NPS shapes differed between AIDR and PIQE, producing noticeably different noise textures that were dose- and phantom size-dependent. CNRLO values were similar between PIQE 512 and PIQE 1024 and were higher than those of AIDR for most scenarios; however, AIDR outperformed PIQE for the 6-mm objects at the medium and high doses. Use of PIQE on the 25-mm disk permits dose reductions in the small phantom without loss of CNRLO. CONCLUSION: PIQE provides substantial image quality improvements over AIDR in phantom-based quantitative measurements. The potential for dose reduction is also noted. PIQE 1024 can be used to improve the spatial resolution over PIQE 512, with no apparent trade-offs in image quality.

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