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Bin Zheng
Researcher at University of Oklahoma
Publications - 398
Citations - 8484
Bin Zheng is an academic researcher from University of Oklahoma. The author has contributed to research in topics: Breast cancer & Feature (computer vision). The author has an hindex of 45, co-authored 355 publications receiving 6866 citations. Previous affiliations of Bin Zheng include Northeastern University (China) & Hangzhou Dianzi University.
Papers
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Journal ArticleDOI
Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms.
Morteza Heidari,Seyedehnafiseh Mirniaharikandehei,Abolfazl Zargari Khuzani,Gopichandh Danala,Yuchen Qiu,Bin Zheng +5 more
TL;DR: It is demonstrated that adding two image preprocessing steps and generating a pseudo color image plays an important role in developing a deep learning CAD scheme of chest X-ray images to improve accuracy in detecting COVID-19 infected pneumonia.
Proceedings ArticleDOI
Computer aided lung cancer diagnosis with deep learning algorithms
TL;DR: This study tested the feasibility of using deep learning algorithms for lung cancer diagnosis with the cases from Lung Image Database Consortium (LIDC) database, including Convolutional Neural Network, Deep Belief Networks, and Stacked Denoising Autoencoder.
Journal ArticleDOI
A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval
Liu Yang,Rong Jin,Lily Mummert,Rahul Sukthankar,Adam Goode,Bin Zheng,Steven C. H. Hoi,Mahadev Satyanarayanan +7 more
TL;DR: This work presents a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities and shows that the boosting framework compares favorably to state-of-the-art approaches fordistance metric learning in retrieval accuracy, with much lower computational cost.
Journal ArticleDOI
IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge
Prasanna Porwal,Prasanna Porwal,Samiksha Pachade,Manesh Kokare,Girish Deshmukh,Jaemin Son,Woong Bae,Lihong Liu,Jianzong Wang,Xinhui Liu,Liangxin Gao,Tian Bo Wu,Jing Xiao,Fengyan Wang,Baocai Yin,Yunzhi Wang,Gopichandh Danala,Linsheng He,Yoon-Ho Choi,Yeong Chan Lee,Sang Hyuk Jung,Zhongyu Li,Xiaodan Sui,Junyan Wu,Xiaolong Li,Ting Zhou,Janos Toth,Agnes Baran,Avinash Kori,Sai Saketh Chennamsetty,Mohammed Safwan,Varghese Alex,Xingzheng Lyu,Li Cheng,Qinhao Chu,Pengcheng Li,Xin Ji,Sanyuan Zhang,Shen Yaxin,Ling Dai,Oindrila Saha,Rachana Sathish,Tânia Melo,Teresa Araújo,Balazs Harangi,Bin Sheng,Ruogu Fang,Debdoot Sheet,Andras Hajdu,Yuanjie Zheng,Ana Maria Mendonça,Shaoting Zhang,Aurélio Campilho,Bin Zheng,Dinggang Shen,Luca Giancardo,Gwenole Quellec,Fabrice Meriaudeau +57 more
TL;DR: The set-up and results of this challenge that is primarily based on Indian Diabetic Retinopathy Image Dataset (IDRiD), which received a positive response from the scientific community, have the potential to enable new developments in retinal image analysis and image-based DR screening in particular.
Journal ArticleDOI
Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis
Wenqing Sun,Bin Zheng,Wei Qian +2 more
TL;DR: The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis with well-tuned parameters and large enough dataset, and the deep learning algorithms can have better performance than current popular CADx.