Investigation of the effectiveness of no-reference metric in image evaluation in nuclear medicine.

Background: In nuclear medicine, normalized mean square error (NMSE) is widely used for image quality evaluation and machine adjustment. However, evaluating clinical images in nuclear medicine using NMSE necessitates acquiring a reference image, which is time consuming and impractical. Therefore, it is necessary to explore no-reference metrics, such as perception-based image quality evaluator (PIQE) and natural image quality evaluator (NIQE), as alternatives for evaluating the quality of clinical images used in nuclear medicine.

Purpose: To examine whether no-reference metrics can be applied to image quality evaluations for clinical images in nuclear medicine.

Methods: Images of the Hoffman Brain Phantom containing 18F-fluoro-2-deoxy-D-glucose (FDG) were obtained using Biograph Vision (Siemens Co., Ltd). From the collected images, 14 images with varying pixel counts and acquisition times were created. Sixteen images were visually evaluated by five image experts and ranked accordingly. Image quality was assessed using NMSE, PIQE, and NIQE, and rankings were calculated based on these scores.

Results: The Spearman's significance test revealed a strong correlation between image quality evaluations using PIQE and visual evaluations by specialists (p<0.0001). PIQE demonstrated comparable performance to image experts in evaluating image quality, suggesting its potential for clinical image quality assessment in nuclear medicine.

Conclusions: PIQE offers a viable method for evaluating image quality in nuclear medicine, presenting a promising alternative to traditional visual inspection methods.