Takafumi Emoto
Overview
Explore the profile of Takafumi Emoto including associated specialties, affiliations and a list of published articles.
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Articles
17
Citations
139
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0
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Recent Articles
1.
Nagayama Y, Ishiuchi S, Inoue T, Funama Y, Shigematsu S, Emoto T, et al.
Eur J Radiol
. 2025 Feb;
184:111953.
PMID: 39908936
Objectives: To evaluate the efficiency of super-resolution deep-learning reconstruction (SR-DLR) optimized for helical body imaging in assessing pancreatic ductal adenocarcinoma (PDAC) using normal-resolution (NR) CT scanner. Methods: Fifty patients with...
2.
Nakato K, Oda S, Yamaguchi S, Sakabe D, Emoto T, Shigematsu S, et al.
J Cardiovasc Comput Tomogr
. 2024 Jul;
19(1):83-84.
PMID: 39025757
No abstract available.
3.
Emoto T, Nagayama Y, Takada S, Sakabe D, Shigematsu S, Goto M, et al.
Phys Eng Sci Med
. 2024 Jun;
47(3):1001-1014.
PMID: 38884668
This study aimed to evaluate the impact of radiation dose and focal spot size on the image quality of super-resolution deep-learning reconstruction (SR-DLR) in comparison with iterative reconstruction (IR) and...
4.
Emoto T, Kidoh M, Oda S, Sakabe D, Morita K, Hatemura M, et al.
Medicine (Baltimore)
. 2024 May;
103(20):e38295.
PMID: 38758838
To assess the diagnostic performance of unenhanced electrocardiogram (ECG)-gated cardiac computed tomography (CT) for detecting myocardial edema, using MRI T2 mapping as the reference standard. This retrospective study protocol was...
5.
Nagayama Y, Emoto T, Kato Y, Kidoh M, Oda S, Sakabe D, et al.
Eur Radiol
. 2023 Jul;
33(12):8488-8500.
PMID: 37432405
Objectives: To evaluate the effect of super-resolution deep-learning-based reconstruction (SR-DLR) on the image quality of coronary CT angiography (CCTA). Methods: Forty-one patients who underwent CCTA using a 320-row scanner were...
6.
Nagayama Y, Emoto T, Hayashi H, Kidoh M, Oda S, Nakaura T, et al.
AJR Am J Roentgenol
. 2023 Jun;
221(5):599-610.
PMID: 37377362
A super-resolution deep learning reconstruction (SR-DLR) algorithm may provide better image sharpness than earlier reconstruction algorithms and thereby improve coronary stent assessment on coronary CTA. The purpose of our study...
7.
Kidoh M, Oda S, Takashio S, Kawano Y, Hayashi H, Morita K, et al.
Radiol Cardiothorac Imaging
. 2023 May;
5(2):e220327.
PMID: 37124644
Purpose: To evaluate the diagnostic performance of myocardium-to-lumen R1 (1/T1) ratio on postcontrast T1 maps for the detection of cardiac amyloidosis in a large patient sample. Materials And Methods: This...
8.
Nagayama Y, Iwashita K, Maruyama N, Uetani H, Goto M, Sakabe D, et al.
Eur Radiol
. 2023 Mar;
33(5):3253-3265.
PMID: 36973431
Objectives: To evaluate the image quality of deep learning-based reconstruction (DLR), model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose (LD) unenhanced head CT and compare it with those...
9.
Goto M, Nagayama Y, Sakabe D, Emoto T, Kidoh M, Oda S, et al.
Acad Radiol
. 2022 Jun;
30(3):431-440.
PMID: 35738988
Rationale And Objectives: To evaluate the image properties of lung-specialized deep-learning-based reconstruction (DLR) and its applicability in ultralow-dose CT (ULDCT) relative to hybrid- (HIR) and model-based iterative-reconstructions (MBIR). Materials And...
10.
Hayashi H, Oda S, Emoto T, Kidoh M, Nagayama Y, Nakaura T, et al.
Eur J Radiol
. 2022 Jun;
153:110386.
PMID: 35661458
Purpose: Myocardial extracellular volume (ECV) measured by cardiac magnetic resonance imaging (MRI) has been suggested as a marker of disease severity in pulmonary hypertension (PH). However, consistency between ECVs quantified...