Showing 721 - 740 results of 901 for search '"Medical imaging"', query time: 0.09s Refine Results
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    TRACE Model: Predicting Treatment Response to Transarterial Chemoembolization in Unresectable Hepatocellular Carcinoma by Wang W, Zhang Q, Cui Y, Zhang S, Li B, Xia T, Song Y, Zhou S, Ye F, Xiao W, Cao K, Chi Y, Qu J, Zhou G, Chen Z, Zhang T, Chen X, Ju S, Wang YC

    Published 2025-01-01
    “…Weilang Wang,1,* Qi Zhang,2,* Ying Cui,1,* Shuhang Zhang,1 Binrong Li,1 Tianyi Xia,1 Yang Song,3 Shuwei Zhou,1 Feng Ye,4 Wenbo Xiao,5 Kun Cao,6 Yuan Chi,7 Jinrong Qu,8 Guofeng Zhou,9,10 Zhao Chen,11 Teng Zhang,12 Xunjun Chen,13 Shenghong Ju,1 Yuan-Cheng Wang1 1Department of Radiology, Zhongda Hospital, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China; 2Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, People’s Republic of China; 3MR Scientific Marketing, Siemens Healthineers Ltd, Shanghai, People’s Republic of China; 4Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 5Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People’s Republic of China; 6Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, People’s Republic of China; 7Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People’s Republic of China; 8Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, People’s Republic of China; 9Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 10Shanghai Institute of Medical Imaging, Shanghai, People’s Republic of China; 11Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 12Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, People’s Republic of China; 13Department of Radiology, The People’s Hospital of Xuyi County, Huaian, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yuan-Cheng Wang, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, 87 Ding Jia Qiao Road, Nanjing, Jiangsu, 210009, People’s Republic of China, Tel +086 25 83272121, Fax +086 25 83311083, Email yuancheng_wang@seu.edu.cnPurpose: To develop and validate a predictive model for predicting six-month outcome by integrating pretreatment MRI features and one-month treatment response after TACE.Methods: A total of 108 patients with 160 hCCs from a single-arm, multicenter clinical trial (NCT03113955) were analyzed and served as the training cohort. …”
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    Uptake and 4-week outcomes of an ‘opt-out’ smoking cessation referral strategy in a London-based lung cancer screening setting by Anthony Edey, Neal Navani, Kitty Chan, Graham Robinson, Janine Zylstra, Paul Robinson, Laura Green, Anand Devaraj, Jane Rowlands, Allan Hackshaw, Carolyn Horst, Arjun Nair, Sam M Janes, Kate Davies, Jeannie Eng, Mamta Ruparel, Samantha L Quaife, Jennifer L Dickson, Magali Taylor, Angshu Bhowmik, Hasti Robbie, Joseph Jacob, Laura Farrelly, Sophie Tisi, Tanya Patrick, Andrew Creamer, Helen Hall, Samanjit Hare, Jon Teague, Samuel M Janes, Esther Arthur-Darkwa, Thea Buchan, Stephen Ellis, Thomas Callender, Rachael Sarpong, John McCabe, Zaheer Mangera, Ethaar El-Emir, Terry O'Shaughnessy, Geoff Bellingan, Nick Screaton, Priyam Verghese, William M Ricketts, Vicky Bowyer, Kylie Gyertson, Fanta Bojang, Claire Levermore, Tania Anastasiadis, Ruth Prendecki, Amyn Bhamani, Malavika Suresh, Judy Airebamen, Alice Cotton, Kaylene Phua, Elodie Murali, Simranjit Mehta, Karen Parry-Billings, Columbus Ife, April Neville, Zahra Hanif, Helen Kiconco, Ricardo McEwen, Dominique Arancon, Nicholas Beech, Derya Ovayolu, Christine Hosein, Sylvia Patricia Enes, Qin April Neville, Aashna Samson, Urja Patel, Fahmida Hoque, Hina Pervez, Sofia Nnorom, Moksud Miah, Julian McKee, Mark Clark, Anant Patel, Sara Lock, Rajesh Banka, Ugo Ekeowa, Charlotte Cash, Tunku Aziz, Alberto Villanueva, Elena Stefan, Charlie Sayer, Navinah Nundlall, Andrew Crossingham, Tanita Limani, Kate Gowers, Andrew Perugia, James Rusius, Anne-Marie Hacker, Monica L Mullin, Evangelos Katsampouris, Chuen R Khaw, Chuen Khaw, Sheetal Karavadra, Alan Shaw, Chris Valerio, Ali Mohammed, Lynsey Gallagher, Mehran Azimbagirad, Burcu Ozaltin, Maureen Browne, Eleanor Hellier, Catherine Nestor

    Published 2025-02-01
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    Research and prospect of reversible data hiding method with contrast enhancement by Yang YANG, Wei-ming ZHANG, ong-dong HOUD, Hui WANG, Neng-hai YU

    Published 2016-04-01
    “…Reversible data hiding methods can recover the cover image losslessly after extracting the secret message from the marked image.Such technology can be used in the certification or the label of military,justice and medical images,which are sensitive and slight modification are not allowed.Especially for the medical images,RDH tech-nology can be used in protecting the privacy of the patient.A series of RDH methods with contrast enhancement ef-fect were introduced and classified into pixel-based histogram methods and prediction-error-based histogram meth-ods according to the type of carrier in RDH scheme.The main purpose of such algorithms was to improve the sub-jective visual quality of marked images and to embed secret data into cover image reversibly meanwhile.These se-ries of algorithms were suitable for the research of privacy protection of medical image.Finally,future development in this direction is prospected through analyzing the advantages and disadvantages of the existing work.…”
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    A Fusion Method of Gabor Wavelet Transform and Unsupervised Clustering Algorithms for Tissue Edge Detection by Burhan Ergen

    Published 2014-01-01
    “…This paper proposes two edge detection methods for medical images by integrating the advantages of Gabor wavelet transform (GWT) and unsupervised clustering algorithms. …”
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