A citation-based method for searching scientific literature

Moi Hoon Yap, Gerard Pons, Joan Marti, Sergi Ganau, Melcior Sentis, Reyer Zwiggelaar, Adrian K Davison, Robert Marti, Moi Hoon Yap, Gerard Pons, Joan Marti, Sergi Ganau, Melcior Sentis, Reyer Zwiggelaar, Adrian K Davison, Robert Marti. IEEE J Biomed Health Inform 2018
Times Cited: 189







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



Times Cited
  Times     Co-cited
Similarity


Dataset of breast ultrasound images.
Walid Al-Dhabyani, Mohammed Gomaa, Hussien Khaled, Aly Fahmy. Data Brief 2019
95
28

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
75
26

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
123
17

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
16

An RDAU-NET model for lesion segmentation in breast ultrasound images.
Zhemin Zhuang, Nan Li, Alex Noel Joseph Raj, Vijayalakshmi G V Mahesh, Shunmin Qiu. PLoS One 2019
30
46

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
14

Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.
Yuzhou Hu, Yi Guo, Yuanyuan Wang, Jinhua Yu, Jiawei Li, Shichong Zhou, Cai Chang. Med Phys 2019
49
26

Large scale deep learning for computer aided detection of mammographic lesions.
Thijs Kooi, Geert Litjens, Bram van Ginneken, Albert Gubern-Mérida, Clara I Sánchez, Ritse Mann, Ard den Heeten, Nico Karssemeijer. Med Image Anal 2017
328
12


Automated diagnosis of breast ultrasonography images using deep neural networks.
Xiaofeng Qi, Lei Zhang, Yao Chen, Yong Pi, Yi Chen, Qing Lv, Zhang Yi. Med Image Anal 2019
50
22

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
27
40


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
29
34

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
131
10

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
34
26

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.
Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla. IEEE Trans Pattern Anal Mach Intell 2017
9

STAN: SMALL TUMOR-AWARE NETWORK FOR BREAST ULTRASOUND IMAGE SEGMENTATION.
Bryar Shareef, Min Xian, Aleksandar Vakanski. Proc IEEE Int Symp Biomed Imaging 2020
14
64

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
31
25

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
91
8

Channel Attention Module With Multiscale Grid Average Pooling for Breast Cancer Segmentation in an Ultrasound Image.
Haeyun Lee, Jinhyoung Park, Jae Youn Hwang. IEEE Trans Ultrason Ferroelectr Freq Control 2020
26
30

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.
Jie-Zhi Cheng, Dong Ni, Yi-Hong Chou, Jing Qin, Chui-Mei Tiu, Yeun-Chung Chang, Chiun-Sheng Huang, Dinggang Shen, Chung-Ming Chen. Sci Rep 2016
253
8

Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images.
Aleksandar Vakanski, Min Xian, Phoebe E Freer. Ultrasound Med Biol 2020
33
24

Computer-aided diagnosis of breast ultrasound images using ensemble learning from convolutional neural networks.
Woo Kyung Moon, Yan-Wei Lee, Hao-Hsiang Ke, Su Hyun Lee, Chiun-Sheng Huang, Ruey-Feng Chang. Comput Methods Programs Biomed 2020
45
17

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
Freddie Bray, Jacques Ferlay, Isabelle Soerjomataram, Rebecca L Siegel, Lindsey A Torre, Ahmedin Jemal. CA Cancer J Clin 2018
7

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
7

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
45
15

Computerized lesion detection on breast ultrasound.
Karen Drukker, Maryellen L Giger, Karla Horsch, Matthew A Kupinski, Carl J Vyborny, Ellen B Mendelson. Med Phys 2002
89
7

Classification of breast cancer histology images using Convolutional Neural Networks.
Teresa Araújo, Guilherme Aresta, Eduardo Castro, José Rouco, Paulo Aguiar, Catarina Eloy, António Polónia, Aurélio Campilho. PLoS One 2017
209
7

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.
Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanislaw Jastrzebski, Thibault Fevry, Joe Katsnelson, Eric Kim,[...]. IEEE Trans Med Imaging 2020
122
7

Deep learning based classification of breast tumors with shear-wave elastography.
Qi Zhang, Yang Xiao, Wei Dai, Jingfeng Suo, Congzhi Wang, Jun Shi, Hairong Zheng. Ultrasonics 2016
86
8

BUSIS: A Benchmark for Breast Ultrasound Image Segmentation.
Yingtao Zhang, Min Xian, Heng-Da Cheng, Bryar Shareef, Jianrui Ding, Fei Xu, Kuan Huang, Boyu Zhang, Chunping Ning, Ying Wang. Healthcare (Basel) 2022
11
63

Deep Learning to Improve Breast Cancer Detection on Screening Mammography.
Li Shen, Laurie R Margolies, Joseph H Rothstein, Eugene Fluder, Russell McBride, Weiva Sieh. Sci Rep 2019
164
7

Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.
Hyuna Sung, Jacques Ferlay, Rebecca L Siegel, Mathieu Laversanne, Isabelle Soerjomataram, Ahmedin Jemal, Freddie Bray. CA Cancer J Clin 2021
7

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
37
16

Cancer statistics, 2019.
Rebecca L Siegel, Kimberly D Miller, Ahmedin Jemal. CA Cancer J Clin 2019
6

Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination.
Ting Xiao, Lei Liu, Kai Li, Wenjian Qin, Shaode Yu, Zhicheng Li. Biomed Res Int 2018
41
14

Medical breast ultrasound image segmentation by machine learning.
Yuan Xu, Yuxin Wang, Jie Yuan, Qian Cheng, Xueding Wang, Paul L Carson. Ultrasonics 2019
50
12

Cancer statistics, 2020.
Rebecca L Siegel, Kimberly D Miller, Ahmedin Jemal. CA Cancer J Clin 2020
6

Screening breast ultrasound: past, present, and future.
Rachel F Brem, Megan J Lenihan, Jennifer Lieberman, Jessica Torrente. AJR Am J Roentgenol 2015
105
6

A novel algorithm for initial lesion detection in ultrasound breast images.
Moi Hoon Yap, Eran A Edirisinghe, Helmut E Bez. J Appl Clin Med Phys 2008
33
18


Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.
Nisreen I R Yassin, Shaimaa Omran, Enas M F El Houby, Hemat Allam. Comput Methods Programs Biomed 2018
77
7

Breast ultrasound region of interest detection and lesion localisation.
Moi Hoon Yap, Manu Goyal, Fatima Osman, Robert Martí, Erika Denton, Arne Juette, Reyer Zwiggelaar. Artif Intell Med 2020
26
23

Segmentation of breast ultrasound image with semantic classification of superpixels.
Qinghua Huang, Yonghao Huang, Yaozhong Luo, Feiniu Yuan, Xuelong Li. Med Image Anal 2020
44
13

CE-Net: Context Encoder Network for 2D Medical Image Segmentation.
Zaiwang Gu, Jun Cheng, Huazhu Fu, Kang Zhou, Huaying Hao, Yitian Zhao, Tianyang Zhang, Shenghua Gao, Jiang Liu. IEEE Trans Med Imaging 2019
311
6

Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.
Yi Wang, Na Wang, Min Xu, Junxiong Yu, Chenchen Qin, Xiao Luo, Xin Yang, Tianfu Wang, Anhua Li, Dong Ni. IEEE Trans Med Imaging 2020
28
21

UNet++: A Nested U-Net Architecture for Medical Image Segmentation.
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang. Deep Learn Med Image Anal Multimodal Learn Clin Decis Support (2018) 2018
584
6

Breast ultrasound image segmentation: a survey.
Qinghua Huang, Yaozhong Luo, Qiangzhi Zhang. Int J Comput Assist Radiol Surg 2017
50
12

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.
Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun. IEEE Trans Pattern Anal Mach Intell 2017
6

Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.
Juan Shan, S Kaisar Alam, Brian Garra, Yingtao Zhang, Tahira Ahmed. Ultrasound Med Biol 2016
57
10


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.