Co-Authors
This is a "connection" page, showing publications co-authored by Bin Zheng and Yuchen Qiu.
Connection Strength
4.878
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A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology. J Xray Sci Technol. 2017; 25(5):751-763.
Score: 0.572
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Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis. Acta Radiol. 2016 Sep; 57(9):1149-55.
Score: 0.532
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Utilizing Pseudo Color Image to Improve the Performance of Deep Transfer Learning-Based Computer-Aided Diagnosis Schemes in Breast Mass Classification. J Imaging Inform Med. 2024 Oct 25.
Score: 0.246
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Improving Performance of Breast Lesion Classification Using a ResNet50 Model Optimized with a Novel Attention Mechanism. Tomography. 2022 Sep 28; 8(5):2411-2425.
Score: 0.213
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Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms. Diagnostics (Basel). 2022 Jun 25; 12(7).
Score: 0.209
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A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods. Bioengineering (Basel). 2022 Jun 15; 9(6).
Score: 0.209
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Recent advances and clinical applications of deep learning in medical image analysis. Med Image Anal. 2022 07; 79:102444.
Score: 0.206
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Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features. Phys Med Biol. 2022 02 21; 67(5).
Score: 0.204
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Using Fourier ptychography microscopy to achieve high-resolution chromosome imaging: an initial evaluation. J Biomed Opt. 2022 01; 27(1).
Score: 0.202
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Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms. Int J Med Inform. 2020 12; 144:104284.
Score: 0.185
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Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients. Comput Methods Programs Biomed. 2020 Dec; 197:105759.
Score: 0.185
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Developing global image feature analysis models to predict cancer risk and prognosis. Vis Comput Ind Biomed Art. 2019; 2(1):17.
Score: 0.175
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Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer. Comput Methods Programs Biomed. 2019 Oct; 179:104995.
Score: 0.171
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Prediction of chemotherapy response in ovarian cancer patients using a new clustered quantitative image marker. Phys Med Biol. 2018 08 06; 63(15):155020.
Score: 0.160
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Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural Networks. Ann Biomed Eng. 2018 Dec; 46(12):1988-1999.
Score: 0.159
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Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm. Phys Med Biol. 2018 01 30; 63(3):035020.
Score: 0.154
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Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy. Acad Radiol. 2017 10; 24(10):1233-1239.
Score: 0.147
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A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images. Comput Methods Programs Biomed. 2017 Jun; 144:97-104.
Score: 0.145
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Computer-aided classification of mammographic masses using visually sensitive image features. J Xray Sci Technol. 2017; 25(1):171-186.
Score: 0.143
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Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome. BMC Med Imaging. 2016 08 31; 16(1):52.
Score: 0.140
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Assessment of performance and reproducibility of applying a content-based image retrieval scheme for classification of breast lesions. Med Phys. 2015 Jul; 42(7):4241-9.
Score: 0.129
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Feature selection for the automated detection of metaphase chromosomes: performance comparison using a receiver operating characteristic method. Anal Cell Pathol (Amst). 2014; 2014:565392.
Score: 0.123
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Evaluations of auto-focusing methods under a microscopic imaging modality for metaphase chromosome image analysis. Anal Cell Pathol (Amst). 2013; 36(1-2):37-44.
Score: 0.108
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Impact of the optical depth of field on cytogenetic image quality. J Biomed Opt. 2012 Sep; 17(9):96017-1.
Score: 0.106
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Automated Quantification of Pneumonia Infected Volume in Lung CT Images: A Comparison with Subjective Assessment of Radiologists. Bioengineering (Basel). 2023 Mar 02; 10(3).
Score: 0.055