Kosuke Morita
Overview
Explore the profile of Kosuke Morita including associated specialties, affiliations and a list of published articles.
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Articles
55
Citations
317
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Recent Articles
1.
Shiraishi K, Nakaura T, Yoshida N, Matsuo K, Kobayashi N, Hokamura M, et al.
J Comput Assist Tomogr
. 2025 Jan;
PMID: 39761494
Objective: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images. Methods: Our...
2.
Morita K, Tahara N, Fukumoto Y
Eur Heart J
. 2024 Sep;
45(43):4663.
PMID: 39288274
No abstract available.
3.
Hokamura M, Nakaura T, Yoshida N, Uetani H, Shiraishi K, Kobayashi N, et al.
Eur J Radiol
. 2024 Jul;
178:111587.
PMID: 39002269
Objectives: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using...
4.
Morita K, Tahara N, Bekki M, Honda A, Tahara A, Maeda-Ogata S, et al.
J Nucl Cardiol
. 2024 Jun;
39:101887.
PMID: 38830569
No abstract available.
5.
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...
6.
Hokamura M, Uetani H, Hamasaki T, Nakaura T, Morita K, Yamashita Y, et al.
Neuroradiology
. 2024 Mar;
66(7):1123-1130.
PMID: 38480538
Purpose: We aimed to evaluate the effect of deep learning-based reconstruction (DLR) on high-spatial-resolution three-dimensional T2-weighted fast asymmetric spin-echo (HR-3D T2-FASE) imaging in the preoperative evaluation of cerebellopontine angle (CPA)...
7.
Sasaki G, Uetani H, Nakaura T, Nakahara K, Morita K, Nagayama Y, et al.
J Comput Assist Tomogr
. 2024 Feb;
48(5):819-825.
PMID: 38346820
Objective: The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance...
8.
Hokamura M, Uetani H, Nakaura T, Matsuo K, Morita K, Nagayama Y, et al.
Neuroradiology
. 2023 Dec;
66(2):217-226.
PMID: 38148334
Purpose: The aim of this study is to assess the effect of super-resolution deep learning-based reconstruction (SR-DLR), which uses k-space properties, on image quality of intracranial time-of-flight (TOF) magnetic resonance...
9.
Matsuo K, Nakaura T, Morita K, Uetani H, Nagayama Y, Kidoh M, et al.
Neuroradiology
. 2023 Sep;
65(11):1619-1629.
PMID: 37673835
Purpose: The purpose of this study is to evaluate the influence of super-resolution deep learning-based reconstruction (SR-DLR), which utilizes k-space data, on the quality of images and the quantitation of...
10.
Morita K, Uetani H, Nakaura T, Yoneyama M, Nagayama Y, Kidoh M, et al.
Magn Reson Imaging
. 2023 Jul;
103:28-36.
PMID: 37406743
Purpose: To evaluate the image quality of the combined technique of compressed sensitivity encoding (CS) and spiral imaging in time-of-flight magnetic resonance angiography (TOF-MRA), which is approximately 2.5 times faster...