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1
Published in 2020 at "Japanese Journal of Radiology"
DOI: 10.1007/s11604-020-01024-1
Abstract: The purpose of the present study was to analyze the left pulmonary artery (LPA) branching pattern of the interlobar portion using three-dimensional CT pulmonary angiography (3D-CTPA) and thin-section CT images, and to attempt to diagrammatize…
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Keywords:
lpa branching;
thin section;
interlobar portion;
portion ... See more keywords
Photo from wikipedia
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1
Published in 2020 at "Academic Radiology"
DOI: 10.1016/j.acra.2020.03.002
Abstract: Rationale and Objectives To retrospectively analyze the chest imaging findings in patients with coronavirus disease 2019 (COVID-19) on thin-section CT. Materials and Methods Fifty-three patients with confirmed COVID-19 infection underwent thin-section CT examination. Two chest…
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Keywords:
thin section;
disease 2019;
2019 covid;
covid ... See more keywords
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0
Published in 2018 at "Journal of Materials Processing Technology"
DOI: 10.1016/j.jmatprotec.2017.08.033
Abstract: Abstract Laser peening of components with thin section is of great concern in industry to improve anti-fatigue properties. This study proposes alternate double-sided laser peening (ADLP) as an optional way for the surface treatment of…
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Keywords:
laser peening;
thin section;
distortion;
geometry ... See more keywords
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Published in 2024 at "Journal of Microscopy"
DOI: 10.1111/jmi.13261
Abstract: The most crucial task of petroleum geology is to explore oil and gas reservoirs in the deep underground. As one of the analysis techniques in petroleum geological research, rock thin section identification method includes particle…
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Keywords:
method;
image;
thin section;
section ... See more keywords
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Published in 2017 at "Radiology"
DOI: 10.1148/radiol.2017161037
Abstract: Purpose To compare the capability of pulmonary thin-section magnetic resonance (MR) imaging with ultrashort echo time (UTE) with that of standard- and reduced-dose thin-section computed tomography (CT) in nodule detection and evaluation of nodule type.…
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Keywords:
reduced dose;
thin section;
imaging ute;
nodule ... See more keywords
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Published in 2024 at "World Journal of Surgical Oncology"
DOI: 10.1186/s12957-024-03354-0
Abstract: To explore the capability and clinical significance of chest thin-section computed tomography (CT) for localization of mammographically detected clustered microcalcifications. A total of 69 patients with 71 mammographically detected clustered microcalcifications received surgical biopsy under…
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Keywords:
mammographically detected;
group;
thin section;
clustered microcalcifications ... See more keywords
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0
Published in 2020 at "American Journal of Neuroradiology"
DOI: 10.3174/ajnr.a6757
Abstract: BACKGROUND AND PURPOSE: Carotid-cavernous fistulas are abnormal vascular shunts that can cause various neurologic or orbital symptoms. The purpose of this retrospective study was to evaluate the diagnostic performance of thin-section MR imaging for carotid…
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Keywords:
cavernous fistula;
carotid cavernous;
thin section;
section imaging ... See more keywords
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Published in 2020 at "Medicina"
DOI: 10.3390/medicina56090479
Abstract: Background and objectives: Thin-section computed tomography (CT) is essential for identifying small bronchi during bronchoscopy using radial endobronchial ultrasound. Some patients should receive an additional CT for a thin-section image. We performed a retrospective study…
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Keywords:
bronchoscopy;
thin section;
group;
ultra ldct ... See more keywords
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Published in 2025 at "Minerals"
DOI: 10.3390/min15090976
Abstract: The accurate classification of rocks is crucial for applications such as earthquake prediction, resource exploration, and geological analysis. Traditional methods rely on expert examination of thin-section images under a microscope, making the process time-consuming and…
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Keywords:
classification;
classification thin;
thin section;
rock ... See more keywords
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0
Published in 2025 at "Minerals"
DOI: 10.3390/min15111112
Abstract: This study presents the application of Mycelial_Net, a biologically inspired deep learning architecture, to the analysis and classification of mineral images in thin section under optical microscopy. The model, inspired by the adaptive connectivity of…
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Keywords:
deep learning;
classification;
inspired deep;
thin section ... See more keywords