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Wyszukujesz frazę ""Radiographic Image Interpretation, Computer-Assisted"" wg kryterium: Temat


Tytuł :
Photorealistic three-dimensional visualization of fusion datasets: cinematic rendering of PET/CT.
Autorzy :
Rowe SP; Department of Radiology and Radiological Science, The Russell H. Morgan, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD, 21287, USA. .
Pomper MG; Department of Radiology and Radiological Science, The Russell H. Morgan, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD, 21287, USA.
Leal JP; Department of Radiology and Radiological Science, The Russell H. Morgan, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD, 21287, USA.
Schneider R; Siemens Healthineers, Forchheim, Germany.
Krüger S; Siemens Healthineers, Forchheim, Germany.
Chu LC; Department of Radiology and Radiological Science, The Russell H. Morgan, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD, 21287, USA.
Fishman EK; Department of Radiology and Radiological Science, The Russell H. Morgan, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Baltimore, MD, 21287, USA.
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Źródło :
Abdominal radiology (New York) [Abdom Radiol (NY)] 2022 Nov; Vol. 47 (11), pp. 3916-3920. Date of Electronic Publication: 2022 Aug 02.
Typ publikacji :
Journal Article
MeSH Terms :
Imaging, Three-Dimensional*/methods
Radiographic Image Interpretation, Computer-Assisted*/methods
Humans ; Male ; Positron Emission Tomography Computed Tomography ; Positron-Emission Tomography ; Radionuclide Imaging ; Somatostatin ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
[Relationship between Image Quality and Reconstruction FOV in Deep Learning Reconstructed Images of CT].
Autorzy :
Odagiri K; Department of Radiology, Division of Medical Technology, Tohoku University Hospital.
Onodera S; Department of Radiology, Division of Medical Technology, Tohoku University Hospital.
Takano H; Department of Radiology, Division of Medical Technology, Tohoku University Hospital.
Kayano S; Department of Radiology, Division of Medical Technology, Tohoku University Hospital.
Sakamoto H; Department of Radiology, Division of Medical Technology, Tohoku University Hospital.
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Źródło :
Nihon Hoshasen Gijutsu Gakkai zasshi [Nihon Hoshasen Gijutsu Gakkai Zasshi] 2022 Oct 20; Vol. 78 (10), pp. 1158-1166. Date of Electronic Publication: 2022 Sep 06.
Typ publikacji :
English Abstract; Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Enhancement*
Radiographic Image Interpretation, Computer-Assisted*/methods
Tomography, X-Ray Computed*
Child ; Humans ; Abdomen/diagnostic imaging
Czasopismo naukowe
Tytuł :
Effects of Model-Based Iterative Reconstruction in Low-Dose Paranasal Computed Tomography: A Comparison with Filtered Back Projection and Hybrid Iterative Reconstruction.
Autorzy :
Tomita H; Department of Radiology, St. Marianna University School of Medicine.
Kuramochi K; Department of Radiology, St. Marianna University School of Medicine.
Fujikawa A; Department of Radiology, St. Marianna University School of Medicine.
Ikeda H; Department of Radiology, Fujita Health University School of Medicine.
Komita M; Department of Radiology, St. Marianna University School of Medicine.
Kurihara Y; Department of Radiology, Machida Municipal Hospital.
Kobayashi Y; Department of Advanced Biomedical Imaging Informatics, St. Marianna University School of Medicine.
Mimura H; Department of Radiology, St. Marianna University School of Medicine.
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Źródło :
Acta medica Okayama [Acta Med Okayama] 2022 Oct; Vol. 76 (5), pp. 511-517.
Typ publikacji :
Journal Article
MeSH Terms :
Radiographic Image Interpretation, Computer-Assisted*/methods
Tomography, X-Ray Computed*/methods
Humans ; Radiation Dosage ; Signal-To-Noise Ratio ; Artifacts ; Algorithms
Czasopismo naukowe
Tytuł :
Quantitative and qualitative assessments of deep learning image reconstruction in low-keV virtual monoenergetic dual-energy CT.
Autorzy :
Xu JJ; Department of Diagnostic Radiology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark. .; Department of Clinical Medicine, University of Copenhagen, 2100, Copenhagen, Denmark. .
Lönn L; Department of Diagnostic Radiology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.; Department of Clinical Medicine, University of Copenhagen, 2100, Copenhagen, Denmark.
Budtz-Jørgensen E; Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
Hansen KL; Department of Diagnostic Radiology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.; Department of Clinical Medicine, University of Copenhagen, 2100, Copenhagen, Denmark.
Ulriksen PS; Department of Diagnostic Radiology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
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Źródło :
European radiology [Eur Radiol] 2022 Oct; Vol. 32 (10), pp. 7098-7107. Date of Electronic Publication: 2022 Jul 27.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Algorithms ; Humans ; Image Processing, Computer-Assisted/methods ; Liver/diagnostic imaging ; Radiation Dosage ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Implementation of cinematic rendering of gastric masses into clinical practice: a pictorial review.
Autorzy :
Brookmeyer C; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N Caroline St, Baltimore, MD, 21287, USA. .
Rowe SP; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N Caroline St, Baltimore, MD, 21287, USA.
Chu LC; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N Caroline St, Baltimore, MD, 21287, USA.
Fishman EK; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N Caroline St, Baltimore, MD, 21287, USA.
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Źródło :
Abdominal radiology (New York) [Abdom Radiol (NY)] 2022 Oct; Vol. 47 (10), pp. 3386-3393. Date of Electronic Publication: 2022 Jul 11.
Typ publikacji :
Journal Article; Review
MeSH Terms :
Radiographic Image Interpretation, Computer-Assisted*/methods
Stomach Neoplasms*/diagnostic imaging
Humans ; Imaging, Three-Dimensional/methods ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Photorealistic Depiction of Intracranial Tumors Using Cinematic Rendering of Volumetric 3T MRI Data.
Autorzy :
Lakhani DA; Department of Radiology (D.A.L.), West Virginia University, 1 Medical Center Drive, Morgantown, West Virginia 26506, USA; Department of Neuroradiology (G.D.), West Virginia University, Morgantown, West Virginia, USA. Electronic address: .
Deib G; Department of Radiology (D.A.L.), West Virginia University, 1 Medical Center Drive, Morgantown, West Virginia 26506, USA; Department of Neuroradiology (G.D.), West Virginia University, Morgantown, West Virginia, USA.
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Źródło :
Academic radiology [Acad Radiol] 2022 Oct; Vol. 29 (10), pp. e211-e218. Date of Electronic Publication: 2022 Jan 13.
Typ publikacji :
Journal Article
MeSH Terms :
Brain Neoplasms*/diagnostic imaging
Radiographic Image Interpretation, Computer-Assisted*/methods
Humans ; Imaging, Three-Dimensional/methods ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
An Automatic Random Walker Algorithm for Segmentation of Ground Glass Opacity Pulmonary Nodules.
Autorzy :
Li X; School of Information Engineering, Guangdong University of Finance & Economics, Guangzhou, Guangdong, China.
Li B; School of Automation Science and Engineering, South China University of Technology, Guangzhou, China.
Yin H; School of Information Engineering, Guangdong University of Finance & Economics, Guangzhou, Guangdong, China.
Xu B; School of Information Engineering, Guangdong University of Finance & Economics, Guangzhou, Guangdong, China.
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Źródło :
Journal of healthcare engineering [J Healthc Eng] 2022 Sep 29; Vol. 2022, pp. 6727957. Date of Electronic Publication: 2022 Sep 29 (Print Publication: 2022).
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Lung Neoplasms*/diagnostic imaging
Radiographic Image Interpretation, Computer-Assisted*/methods
Algorithms ; Humans ; Image Processing, Computer-Assisted/methods ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Deep learning-based reconstruction on cardiac CT yields distinct radiomic features compared to iterative and filtered back projection reconstructions.
Autorzy :
Chun SH; Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
Suh YJ; Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea. .
Han K; Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
Kwon Y; Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, Korea.
Kim AY; Weill Cornell Medicine-Qatar, Doha, Qatar.
Choi BW; Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
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Źródło :
Scientific reports [Sci Rep] 2022 Sep 07; Vol. 12 (1), pp. 15171. Date of Electronic Publication: 2022 Sep 07.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Humans ; Retrospective Studies ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Effects of contrast enhancement boost postprocessing technique in combination with different reconstruction algorithms on the image quality of abdominal CT angiography.
Autorzy :
Xu J; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wang S; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wang X; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: dr_.
Wang Y; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xue H; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: .
Yan J; Canon Medical Systems (China), Beijing 100015, China.
Xu M; Canon Medical Systems (China), Beijing 100015, China.
Jin Z; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Źródło :
European journal of radiology [Eur J Radiol] 2022 Sep; Vol. 154, pp. 110388. Date of Electronic Publication: 2022 Jun 02.
Typ publikacji :
Journal Article
MeSH Terms :
Computed Tomography Angiography*/methods
Radiographic Image Interpretation, Computer-Assisted*/methods
Algorithms ; Humans ; Radiation Dosage ; Retrospective Studies
Czasopismo naukowe
Tytuł :
Easy transfer of digital image data: Principle vs implementation.
Autorzy :
Buchanan A; Professor of Oral Radiology, Department of Oral Biology, Diagnostic Sciences, The Dental College of Georgia at Augusta University, Augusta, GA, USA. Electronic address: .
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Źródło :
Oral surgery, oral medicine, oral pathology and oral radiology [Oral Surg Oral Med Oral Pathol Oral Radiol] 2022 Sep; Vol. 134 (3), pp. 273-275. Date of Electronic Publication: 2022 May 10.
Typ publikacji :
Editorial
MeSH Terms :
Radiographic Image Enhancement*/methods
Radiographic Image Interpretation, Computer-Assisted*/methods
Humans ; Image Processing, Computer-Assisted/methods
Opinia redakcyjna
Tytuł :
Visualization of acute aortic injury with cinematic rendering.
Autorzy :
Al Khalifah A; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, USA. .
Zimmerman SL; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, USA.
Fishman EK; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, USA.
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Źródło :
Emergency radiology [Emerg Radiol] 2022 Dec; Vol. 29 (6), pp. 1043-1048. Date of Electronic Publication: 2022 Sep 01.
Typ publikacji :
Journal Article
MeSH Terms :
Radiographic Image Interpretation, Computer-Assisted*/methods
Vascular System Injuries*
Humans ; Imaging, Three-Dimensional/methods ; Tomography, X-Ray Computed/methods ; Computed Tomography Angiography/methods
Czasopismo naukowe
Tytuł :
Low-dose abdominopelvic computed tomography in patients with lymphoma: An image quality and radiation dose reduction study.
Autorzy :
Yoon S; Department of Radiology, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea.
Yoo KH; Department of Internal Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Park SH; Department of Radiology, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea.
Kim H; Department of Internal Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Lee JH; Department of Internal Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Park J; Department of Internal Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Park SH; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Kim HJ; Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, Ulsan University College of Medicine, Seoul, Korea.
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Źródło :
PloS one [PLoS One] 2022 Aug 11; Vol. 17 (8), pp. e0272356. Date of Electronic Publication: 2022 Aug 11 (Print Publication: 2022).
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Lymphoma*/diagnostic imaging
Radiographic Image Interpretation, Computer-Assisted*/methods
Drug Tapering ; Humans ; Radiation Dosage ; Retrospective Studies ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.
Autorzy :
Nagayama Y; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Goto M; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan.
Sakabe D; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan.
Emoto T; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan.
Shigematsu S; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan.
Oda S; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Tanoue S; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Kidoh M; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Nakaura T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Funama Y; Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan.
Uchimura R; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Takada S; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Hayashi H; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Hatemura M; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan.
Hirai T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
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Źródło :
AJR. American journal of roentgenology [AJR Am J Roentgenol] 2022 Aug; Vol. 219 (2), pp. 315-324. Date of Electronic Publication: 2022 Feb 23.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Algorithms ; Child ; Child, Preschool ; Drug Tapering ; Humans ; Radiation Dosage ; Retrospective Studies ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.
Autorzy :
Greffier J; IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France.
Si-Mohamed S; University of Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, Villeurbanne, France.; Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, Bron, France.
Frandon J; IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France.
Loisy M; IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France.
de Oliveira F; IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France.
Beregi JP; IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France.
Dabli D; IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France.
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Źródło :
Medical physics [Med Phys] 2022 Aug; Vol. 49 (8), pp. 5052-5063. Date of Electronic Publication: 2022 Jun 24.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Algorithms ; Artificial Intelligence ; Drug Tapering ; Humans ; Phantoms, Imaging ; Radiation Dosage ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Fully automated image quality evaluation on patient CT: Multi-vendor and multi-reconstruction study.
Autorzy :
Chun M; Department of Radiation Oncology, Chung-Ang University Gwang Myeong Hospital, Gyeonggi-do, Republic of Korea.; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
Choi JH; Department of Radiation Oncology, Chung-Ang University College of Medicine, Seoul, Republic of Korea.
Kim S; Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea.
Ahn C; Department of Transdisciplinary Studies, Program in Biomedical Radiation Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea.; ClariPi Research, Seoul, Republic of Korea.
Kim JH; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.; Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea.; Department of Transdisciplinary Studies, Program in Biomedical Radiation Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea.; ClariPi Research, Seoul, Republic of Korea.; Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.; Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.; Center for Medical-IT Convergence Technology Research, Advanced Institutes of Convergence Technology, Suwon, Republic of Korea.
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Źródło :
PloS one [PLoS One] 2022 Jul 20; Vol. 17 (7), pp. e0271724. Date of Electronic Publication: 2022 Jul 20 (Print Publication: 2022).
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Radiographic Image Interpretation, Computer-Assisted*/methods
Tomography, X-Ray Computed*/methods
Algorithms ; Humans ; Radiation Dosage
Czasopismo naukowe
Tytuł :
The evaluation of the reduction of radiation dose via deep learning-based reconstruction for cadaveric human lung CT images.
Autorzy :
Miyata T; Department of Future Diagnastic Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita-City, Osaka, 565-0871, Japan.
Yanagawa M; Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka, 565-0871, Japan. .
Kikuchi N; Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka, 565-0871, Japan.
Yamagata K; Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka, 565-0871, Japan.
Sato Y; Department of Radiology, Suita Municipal Hospital, 5-7 Kishibeshinmati, Suita-city, Osaka, 564-8567, Japan.
Yoshida Y; Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka, 565-0871, Japan.
Tsubamoto M; Department of Radiology, Nishinomiya Municipal Central Hospital, 8-24 Hayashidacho, Nishinomiya City, Hyogo, 663-8014, Japan.
Tomiyama N; Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka, 565-0871, Japan.
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Źródło :
Scientific reports [Sci Rep] 2022 Jul 20; Vol. 12 (1), pp. 12422. Date of Electronic Publication: 2022 Jul 20.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Algorithms ; Cadaver ; Humans ; Lung/diagnostic imaging ; Radiation Dosage ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Deep learning versus iterative reconstruction on image quality and dose reduction in abdominal CT: a live animal study.
Autorzy :
Zhang JZ; Math, Science, and Technology Center, Lexington, KY 40513, United States of America.
Ganesh H; Department of Radiology, University of Kentucky College of Medicine, Lexington, KY 40536 United States of America.
Raslau FD; Department of Radiology, University of Kentucky College of Medicine, Lexington, KY 40536 United States of America.
Nair R; Department of Radiology, University of Kentucky College of Medicine, Lexington, KY 40536 United States of America.
Escott E; Department of Radiology, University of Kentucky College of Medicine, Lexington, KY 40536 United States of America.
Wang C; Department of Statistics, University of Kentucky, Lexington, KY 40536, United States of America.
Wang G; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, United States of America.
Zhang J; Department of Radiology, University of Kentucky College of Medicine, Lexington, KY 40536 United States of America.
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Źródło :
Physics in medicine and biology [Phys Med Biol] 2022 Jul 08; Vol. 67 (14). Date of Electronic Publication: 2022 Jul 08.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Abdomen/diagnostic imaging ; Algorithms ; Animals ; Drug Tapering ; Phantoms, Imaging ; Radiation Dosage ; Sheep ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Application of computer-aided detection (CAD) software to automatically detect nodules under SDCT and LDCT scans with different parameters.
Autorzy :
Hu Q; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China.
Chen C; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China.
Kang S; Department of Radiology, Shenzhen Maternity & Child Healthcare Hospital, Affiliated to Southern Medical University, Hongli, Shenzhen, 518028, PR China.
Sun Z; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China.
Wang Y; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China.
Xiang M; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China.
Guan H; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China.
Xia L; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China. Electronic address: .
Wang S; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan, 430030, PR China. Electronic address: .
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Źródło :
Computers in biology and medicine [Comput Biol Med] 2022 Jul; Vol. 146, pp. 105538. Date of Electronic Publication: 2022 Apr 17.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Radiographic Image Interpretation, Computer-Assisted*/methods
Tomography, X-Ray Computed*/methods
Algorithms ; Humans ; Radiation Dosage ; Radionuclide Imaging ; Software
Czasopismo naukowe
Tytuł :
Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT.
Autorzy :
Son W; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
Kim M; School of Biomedical Convergence Engineering, Pusan National University, Busan, Korea.
Hwang JY; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.; Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, College of Medicine, Pusan National University, Yangsan, Korea. .
Kim YW; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
Park C; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
Choo KS; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
Kim TU; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
Jang JY; Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
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Źródło :
Korean journal of radiology [Korean J Radiol] 2022 Jul; Vol. 23 (7), pp. 752-762. Date of Electronic Publication: 2022 May 27.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Radiographic Image Interpretation, Computer-Assisted*/methods
Adolescent ; Algorithms ; Child ; Child, Preschool ; Humans ; Image Processing, Computer-Assisted ; Male ; Radiation Dosage ; Retrospective Studies ; Tomography, X-Ray Computed/methods
Czasopismo naukowe
Tytuł :
Analysis of a monocentric computed tomography dosimetric database using a radiation dose index monitoring software: dose levels and alerts before and after the implementation of the adaptive statistical iterative reconstruction on CT images.
Autorzy :
Fusco R; Medical Oncology Division, Igea SpA, Napoli, Italy.
Setola SV; Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy.
Raiano N; Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy.
Granata V; Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy.
Cerciello V; Health Physics Unit, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy.
Pecori B; Radioprotection and innovative technologies, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131, Naples, Italy. .
Petrillo A; Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy.
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Źródło :
La Radiologia medica [Radiol Med] 2022 Jul; Vol. 127 (7), pp. 733-742. Date of Electronic Publication: 2022 May 17.
Typ publikacji :
Journal Article
MeSH Terms :
Radiographic Image Interpretation, Computer-Assisted*/methods
Tomography, X-Ray Computed*/methods
Algorithms ; Humans ; Radiation Dosage ; Retrospective Studies ; Software
Czasopismo naukowe

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