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For: Choe J, Hwang HJ, Seo JB, Lee SM, Yun J, Kim MJ, Jeong J, Lee Y, Jin K, Park R, Kim J, Jeon H, Kim N, Yi J, Yu D, Kim B. Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT. Radiology 2021;:204164. [PMID: 34636634 DOI: 10.1148/radiol.2021204164] [Cited by in Crossref: 9] [Cited by in F6Publishing: 11] [Article Influence: 4.5] [Reference Citation Analysis]
Number Citing Articles
1 Özbay E, Özbay FA. Interpretable pap-smear image retrieval for cervical cancer detection with rotation invariance mask generation deep hashing. Comput Biol Med 2023;154:106574. [PMID: 36738706 DOI: 10.1016/j.compbiomed.2023.106574] [Reference Citation Analysis]
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6 Aoki R, Iwasawa T, Saka T, Yamashiro T, Utsunomiya D, Misumi T, Baba T, Ogura T. Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis. Diagnostics (Basel) 2022;12. [PMID: 36553045 DOI: 10.3390/diagnostics12123038] [Reference Citation Analysis]
7 Vishraj R, Gupta S, Singh S. A comprehensive review of content-based image retrieval systems using deep learning and hand-crafted features in medical imaging: Research challenges and future directions. Computers and Electrical Engineering 2022;104:108450. [DOI: 10.1016/j.compeleceng.2022.108450] [Reference Citation Analysis]
8 Choe J, Lee SM, Hwang HJ, Lee SM, Yun J, Kim N, Seo JB. Artificial Intelligence in Lung Imaging. Semin Respir Crit Care Med 2022;43:946-60. [PMID: 36174647 DOI: 10.1055/s-0042-1755571] [Reference Citation Analysis]
9 Kumar V. Analysis of CNN features with multiple machine learning classifiers in diagnosis of monkepox from digital skin images.. [DOI: 10.1101/2022.09.11.22278797] [Reference Citation Analysis]
10 Jardim S, António J, Mora C, Almeida A. A Novel Trademark Image Retrieval System Based on Multi-Feature Extraction and Deep Networks. J Imaging 2022;8:238. [PMID: 36135404 DOI: 10.3390/jimaging8090238] [Reference Citation Analysis]
11 Higaki A, Kawaguchi N, Kurokawa T, Okabe H, Kazatani T, Kido S, Aono T, Matsuda K, Tanaka Y, Hosokawa S, Kosaki T, Kawamura G, Shigematsu T, Kawada Y, Hiasa G, Yamada T, Okayama H. Content-based image retrieval for the diagnosis of myocardial perfusion imaging using a deep convolutional autoencoder. J Nucl Cardiol 2022. [PMID: 35802346 DOI: 10.1007/s12350-022-03030-4] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
12 Röhrich S, Heidinger BH, Prayer F, Weber M, Krenn M, Zhang R, Sufana J, Scheithe J, Kanbur I, Korajac A, Pötsch N, Raudner M, Al-Mukhtar A, Fueger BJ, Milos RI, Scharitzer M, Langs G, Prosch H. Impact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease. Eur Radiol 2022. [PMID: 35779087 DOI: 10.1007/s00330-022-08973-3] [Reference Citation Analysis]
13 Yang C, Chen C, Kuo Y, Ko C, Wu W, Liang C, Yun C, Huang W. Radiomics for the Prediction of Response to Antifibrotic Treatment in Patients with Idiopathic Pulmonary Fibrosis: A Pilot Study. Diagnostics 2022;12:1002. [DOI: 10.3390/diagnostics12041002] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
14 Choudhury S, Chohan A, Dadhwal R, Vakil AP, Franco R, Taweesedt PT. Applications of artificial intelligence in common pulmonary diseases. Artif Intell Med Imaging 2022; 3(1): 1-7 [DOI: 10.35711/aimi.v3.i1.1] [Reference Citation Analysis]
15 Nguyen K, Nguyen HH, Tiulpin A. AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching. Lecture Notes in Computer Science 2022. [DOI: 10.1007/978-3-031-16452-1_69] [Reference Citation Analysis]