A citation-based method for searching scientific literature

Vikash Gupta, Mutlu Demirer, Matthew Bigelow, Kevin J Little, Sema Candemir, Luciano M Prevedello, Richard D White, Thomas P O'Donnell, Michael Wels, Barbaros S Erdal. J Digit Imaging 2020
Times Cited: 5







List of co-cited articles
6 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.
Hoo-Chang Shin, Holger R Roth, Mingchen Gao, Le Lu, Ziyue Xu, Isabella Nogues, Jianhua Yao, Daniel Mollura, Ronald M Summers. IEEE Trans Med Imaging 2016
915
60


Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis.
Veronika Cheplygina, Marleen de Bruijne, Josien P W Pluim. Med Image Anal 2019
118
40

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Nima Tajbakhsh, Jae Y Shin, Suryakanth R Gurudu, R Todd Hurst, Christopher B Kendall, Michael B Gotway, Jianming Liang. IEEE Trans Med Imaging 2016
516
40

A survey on deep learning in medical image analysis.
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A W M van der Laak, Bram van Ginneken, Clara I Sánchez. Med Image Anal 2017
40

Deep Learning: A Primer for Radiologists.
Gabriel Chartrand, Phillip M Cheng, Eugene Vorontsov, Michal Drozdzal, Simon Turcotte, Christopher J Pal, Samuel Kadoury, An Tang. Radiographics 2017
363
40

Artificial Intelligence Medical Ultrasound Equipment: Application of Breast Lesions Detection.
Xuesheng Zhang, Xiaona Lin, Zihao Zhang, Licong Dong, Xinlong Sun, Desheng Sun, Kehong Yuan. Ultrason Imaging 2020
5
20

A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound: Added value for the inexperienced breast radiologist.
Hee Jeong Park, Sun Mi Kim, Bo La Yun, Mijung Jang, Bohyoung Kim, Ja Yoon Jang, Jong Yoon Lee, Soo Hyun Lee. Medicine (Baltimore) 2019
28
20

Differential Data Augmentation Techniques for Medical Imaging Classification Tasks.
Zeshan Hussain, Francisco Gimenez, Darvin Yi, Daniel Rubin. AMIA Annu Symp Proc 2018
65
20

Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images.
Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Sun Mi Kim, Kyoung Mu Lee. IEEE Trans Med Imaging 2019
22
20

Breast ultrasound lesions recognition: end-to-end deep learning approaches.
Moi Hoon Yap, Manu Goyal, Fatima M Osman, Robert Martí, Erika Denton, Arne Juette, Reyer Zwiggelaar. J Med Imaging (Bellingham) 2019
20
20


Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.
Richard Ha, Christine Chin, Jenika Karcich, Michael Z Liu, Peter Chang, Simukayi Mutasa, Eduardo Pascual Van Sant, Ralph T Wynn, Eileen Connolly, Sachin Jambawalikar. J Digit Imaging 2019
28
20

Performance and Reading Time of Automated Breast US with or without Computer-aided Detection.
Shanling Yang, Xican Gao, Liwen Liu, Rui Shu, Jingru Yan, Ge Zhang, Yao Xiao, Yan Ju, Ni Zhao, Hongping Song. Radiology 2019
14
20

Breast density implications and supplemental screening.
Athina Vourtsis, Wendie A Berg. Eur Radiol 2019
47
20

BI-RADS lexicon for US and mammography: interobserver variability and positive predictive value.
Elizabeth Lazarus, Martha B Mainiero, Barbara Schepps, Susan L Koelliker, Linda S Livingston. Radiology 2006
296
20

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.
Li-Qiang Zhou, Xing-Long Wu, Shu-Yan Huang, Ge-Ge Wu, Hua-Rong Ye, Qi Wei, Ling-Yun Bao, You-Bin Deng, Xing-Rui Li, Xin-Wu Cui,[...]. Radiology 2020
48
20

Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.
Tomoyuki Fujioka, Kazunori Kubota, Mio Mori, Yuka Kikuchi, Leona Katsuta, Mai Kasahara, Goshi Oda, Toshiyuki Ishiba, Tsuyoshi Nakagawa, Ukihide Tateishi. Jpn J Radiol 2019
46
20

Automated and real-time segmentation of suspicious breast masses using convolutional neural network.
Viksit Kumar, Jeremy M Webb, Adriana Gregory, Max Denis, Duane D Meixner, Mahdi Bayat, Dana H Whaley, Mostafa Fatemi, Azra Alizad. PLoS One 2018
22
20

Tumor detection in automated breast ultrasound images using quantitative tissue clustering.
Woo Kyung Moon, Chung-Ming Lo, Rong-Tai Chen, Yi-Wei Shen, Jung Min Chang, Chiun-Sheng Huang, Jeon-Hor Chen, Wei-Wen Hsu, Ruey-Feng Chang. Med Phys 2014
23
20


Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography.
Ji Soo Choi, Boo Kyung Han, Eun Sook Ko, Jung Min Bae, Eun Young Ko, So Hee Song, Mi Ri Kwon, Jung Hee Shin, Soo Yeon Hahn. Korean J Radiol 2019
32
20

Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making.
Alexander Ciritsis, Cristina Rossi, Matthias Eberhard, Magda Marcon, Anton S Becker, Andreas Boss. Eur Radiol 2019
35
20

Projection of Breast Cancer Burden due to Reproductive/Lifestyle Changes in Korean Women (2013-2030) Using an Age-Period-Cohort Model.
Joo Eun Lee, Sang Ah Lee, Tae Hyun Kim, Sohee Park, Yoon Soo Choy, Yeong Jun Ju, Eun-Cheol Park. Cancer Res Treat 2018
10
20

Computer-aided tumor detection based on multi-scale blob detection algorithm in automated breast ultrasound images.
Woo Kyung Moon, Yi-Wei Shen, Min Sun Bae, Chiun-Sheng Huang, Jeon-Hor Chen, Ruey-Feng Chang. IEEE Trans Med Imaging 2013
34
20

Rapid image stitching and computer-aided detection for multipass automated breast ultrasound.
Ruey-Feng Chang, Kuang-Che Chang-Chien, Etsuo Takada, Chiun-Sheng Huang, Yi-Hong Chou, Chen-Ming Kuo, Jeon-Hor Chen. Med Phys 2010
22
20

Computer-aided tumor detection in automated breast ultrasound using a 3-D convolutional neural network.
Woo Kyung Moon, Yao-Sian Huang, Chin-Hua Hsu, Ting-Yin Chang Chien, Jung Min Chang, Su Hyun Lee, Chiun-Sheng Huang, Ruey-Feng Chang. Comput Methods Programs Biomed 2020
8
20


The California breast density information group: a collaborative response to the issues of breast density, breast cancer risk, and breast density notification legislation.
Elissa R Price, Jonathan Hargreaves, Jafi A Lipson, Edward A Sickles, R James Brenner, Karen K Lindfors, Bonnie N Joe, Jessica W T Leung, Stephen A Feig, Lawrence W Bassett,[...]. Radiology 2013
69
20

Weakly supervised learning of a classifier for unusual event detection.
Mark Jäger, Christian Knoll, Fred A Hamprecht. IEEE Trans Image Process 2008
4
25

Breast mass classification in sonography with transfer learning using a deep convolutional neural network and color conversion.
Michal Byra, Michael Galperin, Haydee Ojeda-Fournier, Linda Olson, Mary O'Boyle, Christopher Comstock, Michael Andre. Med Phys 2019
56
20

Computer-aided diagnosis system for breast ultrasound images using deep learning.
Hiroki Tanaka, Shih-Wei Chiu, Takanori Watanabe, Setsuko Kaoku, Takuhiro Yamaguchi. Phys Med Biol 2019
23
20

Screening breast ultrasound: past, present, and future.
Rachel F Brem, Megan J Lenihan, Jennifer Lieberman, Jessica Torrente. AJR Am J Roentgenol 2015
91
20

Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation.
Tsung-Chen Chiang, Yao-Sian Huang, Rong-Tai Chen, Chiun-Sheng Huang, Ruey-Feng Chang. IEEE Trans Med Imaging 2019
20
20

Operator dependence of physician-performed whole-breast US: lesion detection and characterization.
Wendie A Berg, Jeffrey D Blume, Jean B Cormack, Ellen B Mendelson. Radiology 2006
116
20

Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer.
Xueyi Zheng, Zhao Yao, Yini Huang, Yanyan Yu, Yun Wang, Yubo Liu, Rushuang Mao, Fei Li, Yang Xiao, Yuanyuan Wang,[...]. Nat Commun 2020
75
20

Axillary Nodal Evaluation in Breast Cancer: State of the Art.
Jung Min Chang, Jessica W T Leung, Linda Moy, Su Min Ha, Woo Kyung Moon. Radiology 2020
31
20

Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.
Anton S Becker, Michael Mueller, Elina Stoffel, Magda Marcon, Soleen Ghafoor, Andreas Boss. Br J Radiol 2018
47
20

Development of a fully automatic scheme for detection of masses in whole breast ultrasound images.
Yuji Ikedo, Daisuke Fukuoka, Takeshi Hara, Hiroshi Fujita, Etsuo Takada, Tokiko Endo, Takako Morita. Med Phys 2007
45
20

National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium.
Constance D Lehman, Robert F Arao, Brian L Sprague, Janie M Lee, Diana S M Buist, Karla Kerlikowske, Louise M Henderson, Tracy Onega, Anna N A Tosteson, Garth H Rauscher,[...]. Radiology 2017
211
20

Awareness of breast density and its impact on breast cancer detection and risk.
Deborah J Rhodes, Carmen Radecki Breitkopf, Jeanette Y Ziegenfuss, Sarah M Jenkins, Celine M Vachon. J Clin Oncol 2015
72
20

Prediction of Cancer Incidence and Mortality in Korea, 2020.
Kyu-Won Jung, Young-Joo Won, Seri Hong, Hyun-Joo Kong, Eun Sook Lee. Cancer Res Treat 2020
65
20

An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets.
Hyunkwang Lee, Sehyo Yune, Mohammad Mansouri, Myeongchan Kim, Shahein H Tajmir, Claude E Guerrier, Sarah A Ebert, Stuart R Pomerantz, Javier M Romero, Shahmir Kamalian,[...]. Nat Biomed Eng 2019
99
20

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.
Beau Norgeot, Giorgio Quer, Brett K Beaulieu-Jones, Ali Torkamani, Raquel Dias, Milena Gianfrancesco, Rima Arnaout, Isaac S Kohane, Suchi Saria, Eric Topol,[...]. Nat Med 2020
69
20

Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.
Richard Ha, Peter Chang, Jenika Karcich, Simukayi Mutasa, Eduardo Pascual Van Sant, Eileen Connolly, Christine Chin, Bret Taback, Michael Z Liu, Sachin Jambawalikar. Ann Surg Oncol 2018
12
20

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks.
Moi Hoon Yap, Gerard Pons, Joan Marti, Sergi Ganau, Melcior Sentis, Reyer Zwiggelaar, Adrian K Davison, Robert Marti, Moi Hoon Yap, Gerard Pons,[...]. IEEE J Biomed Health Inform 2018
118
20

A deep learning framework for supporting the classification of breast lesions in ultrasound images.
Seokmin Han, Ho-Kyung Kang, Ja-Yeon Jeong, Moon-Ho Park, Wonsik Kim, Won-Chul Bang, Yeong-Kyeong Seong. Phys Med Biol 2017
94
20

The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart.
Carissa G Fonseca, Michael Backhaus, David A Bluemke, Randall D Britten, Jae Do Chung, Brett R Cowan, Ivo D Dinov, J Paul Finn, Peter J Hunter, Alan H Kadish,[...]. Bioinformatics 2011
119
20

Standardized image interpretation and post-processing in cardiovascular magnetic resonance - 2020 update : Society for Cardiovascular Magnetic Resonance (SCMR): Board of Trustees Task Force on Standardized Post-Processing.
Jeanette Schulz-Menger, David A Bluemke, Jens Bremerich, Scott D Flamm, Mark A Fogel, Matthias G Friedrich, Raymond J Kim, Florian von Knobelsdorff-Brenkenhoff, Christopher M Kramer, Dudley J Pennell,[...]. J Cardiovasc Magn Reson 2020
163
20

UK Biobank's cardiovascular magnetic resonance protocol.
Steffen E Petersen, Paul M Matthews, Jane M Francis, Matthew D Robson, Filip Zemrak, Redha Boubertakh, Alistair A Young, Sarah Hudson, Peter Weale, Steve Garratt,[...]. J Cardiovasc Magn Reson 2016
103
20


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.