Performance of clinically available deep learning image reconstruction in computed tomography: a phantom study-Reference-Cited by-同舟云学术

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Performance of clinically available deep learning image reconstruction in computed tomography: a phantom study

Published:2020-12-16 Issue:06 Volume:7 Page:
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Kawashima Hiroki¹,Ichikawa Katsuhiro¹,Takata Tadanori²,Mitsui Wataru²,Ueta Hiroshi²,Yoneda Norihide³,Kobayashi Satoshi¹

Affiliation:

1. Kanazawa University, Institute of Medical, Pharmaceutical, and Health Sciences, Faculty of Health Sc

2. Kanazawa University Hospital, Radiology Division, Kanazawa

3. Kanazawa University Graduate School of Medical Science, Department of Radiology, Kanazawa

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology Nuclear Medicine and imaging

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2. [CT] 6. The Current Situation of AI Image Reconstruction in CT;Japanese Journal of Radiological Technology;2024-02-20

3. A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results;Journal of Digital Imaging;2023-08-14

4. Spatial resolution, noise properties, and detectability index of a deep learning reconstruction algorithm for dual‐energy CT of the abdomen;Medical Physics;2023-02-21

5. Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose4: a phantom study at different dose levels;Physica Medica;2023-02

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