Noise power spectrum properties of deep learning-based reconstruction and iterative reconstruction algorithms: Phantom and clinical study.

Yoshinori Funama¹, Takeshi Nakaura², Akira Hasegawa³, Daisuke Sakabe⁴, Seitaro Oda², Masafumi Kidoh², Yasunori Nagayama², Toshinori Hirai²

¹Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan. Electronic address: funama@kumamoto-u.ac.jp.

²Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan.

³Department of Radiological Technology, National Cancer Center Japan, Tokyo, Japan; AlgoMedica, Inc., Sunnyvale, CA, USA.

⁴Department of Radiology, Kumamoto University Hospital, Kumamoto, Japan.

PubMed DOI

Abstract

PURPOSE: To compare the noise power spectrum (NPS) properties and perform a qualitative analysis of hybrid iterative reconstruction (IR), model-based IR (MBIR), and deep learning-based reconstruction (DLR) at a similar noise level in clinical study and compare these outcomes with those in phantom study. METHODS: A Catphan phantom with an external body ring was used in the phantom study. In the cl…

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