Takumasa Tsuji
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Explore the profile of Takumasa Tsuji including associated specialties, affiliations and a list of published articles.
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9
Citations
52
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Recent Articles
1.
Tsuji T, Yoshida S, Hommyo M, Oyama A, Kumagai S, Shiraishi K, et al.
J Imaging Inform Med
. 2024 Dec;
PMID: 39633213
Cone beam computed tomography (CBCT) images are convenient representations for obtaining information about patients' internal organs, but their lower image quality than those of treatment planning CT images constitutes an...
2.
Hirata Y, Tsuji T, Kotoku J, Sata M, Kusunose K
Heart
. 2024 Jan;
110(8):586-593.
PMID: 38296266
Objective: The classification of pulmonary hypertension (PH) is crucial for determining the appropriate therapeutic strategy. We investigated whether machine learning (ML) algorithms may assist in echocardiographic PH prediction, where current...
3.
Kusunose K, Tsuji T, Hirata Y, Takahashi T, Sata M, Sato K, et al.
Eur Heart J Open
. 2024 Jan;
4(1):oead136.
PMID: 38188937
Aims: The aim of this study was to identify phenotypes with potential prognostic significance in aortic stenosis (AS) patients after transcatheter aortic valve replacement (TAVR) through a clustering approach. Methods...
4.
Kusunose K, Hirata Y, Yamaguchi N, Kosaka Y, Tsuji T, Kotoku J, et al.
Front Cardiovasc Med
. 2023 Jun;
10:1081628.
PMID: 37273880
Background: A deep learning (DL) model based on a chest x-ray was reported to predict elevated pulmonary artery wedge pressure (PAWP) as heart failure (HF). Objectives: The aim of this...
5.
Tsuji T, Hirata Y, Kusunose K, Sata M, Kumagai S, Shiraishi K, et al.
BMC Med Imaging
. 2023 May;
23(1):62.
PMID: 37161392
Background: This study was conducted to alleviate a common difficulty in chest X-ray image diagnosis: The attention region in a convolutional neural network (CNN) does not often match the doctor's...
6.
Kusunose K, Hirata Y, Yamaguchi N, Kosaka Y, Tsuji T, Kotoku J, et al.
Front Cardiovasc Med
. 2022 Jul;
9:891703.
PMID: 35783826
Background: Stress echocardiography is an emerging tool used to detect exercise-induced pulmonary hypertension (EIPH). However, facilities that can perform stress echocardiography are limited by issues such as cost and equipment....
7.
Hirata Y, Kusunose K, Tsuji T, Fujimori K, Kotoku J, Sata M
Can J Cardiol
. 2021 Feb;
37(8):1198-1206.
PMID: 33609716
Background: To accurately diagnose and control heart failure (HF), it is important to carry out a simple assessment of elevated pulmonary arterial wedge pressure (PAWP). The aim of this study...
8.
Kusunose K, Hirata Y, Tsuji T, Kotoku J, Sata M
Sci Rep
. 2020 Nov;
10(1):19311.
PMID: 33203947
Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of artificial intelligence (AI) to the chest X-ray (CXR) could identify...
9.
Tsuji T, Hirose Y, Fujimori K, Hirose T, Oyama A, Saikawa Y, et al.
BMC Ophthalmol
. 2020 Mar;
20(1):114.
PMID: 32192460
Background: Classification of optical coherence tomography (OCT) images can be achieved with high accuracy using classical convolution neural networks (CNN), a commonly used deep learning network for computer-aided diagnosis. Classical...