Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration-Reference-Cited by-同舟云学术

Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration

Published:2021-06-15 Issue:1 Volume:32 Page:384-394
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Noda Yoshifumi^ORCID,Kawai Nobuyuki,Nagata Shoma,Nakamura Fumihiko,Mori Takayuki,Miyoshi Toshiharu,Suzuki Ryosuke,Kitahara Fumiya,Kato Hiroki,Hyodo Fuminori,Matsuo Masayuki

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-021-08121-3.pdf

Reference25 articles.

1. Tempero MA, Malafa M, AI-Hawary M et al (2021) Pancreatic adenocarcinoma, version 2.2021, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw 19:439–457

2. Noda Y, Goshima S, Miyoshi T et al (2018) Assessing chemotherapeutic response in pancreatic ductal adenocarcinoma: histogram analysis of iodine concentration and CT number in single-source dual-energy CT. AJR Am J Roentgenol 211:1221–1226

3. Greffier J, Frandon J, Larbi A, Beregi JP, Pereira F (2020) CT iterative reconstruction algorithms: a task-based image quality assessment. Eur Radiol 30:487–500

4. Tang H, Liu Z, Hu Z et al (2019) Clinical value of a new generation adaptive statistical iterative reconstruction (ASIR-V) in the diagnosis of pulmonary nodule in low-dose chest CT. Br J Radiol 92:20180909

5. Kim HG, Lee HJ, Lee SK, Kim HJ, Kim MJ (2017) Head CT: image quality improvement with ASIR-V using a reduced radiation dose protocol for children. Eur Radiol 27:3609–3617

Cited by 30 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Vision transformer promotes cancer diagnosis: A comprehensive review;Expert Systems with Applications;2024-10

2. Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity;Acta Radiologica;2024-07-21

3. Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT;BMC Medical Imaging;2024-06-26

4. Improved vascular depiction and image quality through deep learning reconstruction of CT hepatic arteriography during transcatheter arterial chemoembolization;Japanese Journal of Radiology;2024-06-18

5. Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs—A Preliminary Study;Journal of Imaging Informatics in Medicine;2024-03-01