Bin Zheng to Mammography
This is a "connection" page, showing publications Bin Zheng has written about Mammography.
Connection Strength
7.322
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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: 0.739
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Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk. Phys Med Biol. 2018 05 15; 63(10):105005.
Score: 0.569
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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: 0.558
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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: 0.518
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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: 0.518
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Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions. Phys Med Biol. 2017 01 21; 62(2):358-376.
Score: 0.517
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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: 0.466
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A new approach to develop computer-aided detection schemes of digital mammograms. Phys Med Biol. 2015 Jun 07; 60(11):4413-27.
Score: 0.462
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Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk. Ann Biomed Eng. 2015 Oct; 43(10):2416-28.
Score: 0.459
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A new and fast image feature selection method for developing an optimal mammographic mass detection scheme. Med Phys. 2014 Aug; 41(8):081906.
Score: 0.438
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Reduction of false-positive recalls using a computerized mammographic image feature analysis scheme. Phys Med Biol. 2014 Aug 07; 59(15):4357-73.
Score: 0.436
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Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model. Int J Comput Assist Radiol Surg. 2014 Nov; 9(6):1005-20.
Score: 0.427
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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: 0.193
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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: 0.155
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Classification of Breast Masses Using a Computer-Aided Diagnosis Scheme of Contrast Enhanced Digital Mammograms. Ann Biomed Eng. 2018 Sep; 46(9):1419-1431.
Score: 0.142
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Detectability comparison of simulated tumors in digital breast tomosynthesis using high-energy X-ray inline phase sensitive and commercial imaging systems. Phys Med. 2018 Mar; 47:34-41.
Score: 0.140
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Detectability comparison between a high energy x-ray phase sensitive and mammography systems in imaging phantoms with varying glandular-adipose ratios. Phys Med Biol. 2017 05 07; 62(9):3523-3538.
Score: 0.132
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Association between computed tissue density asymmetry in bilateral mammograms and near-term breast cancer risk. Breast J. 2014 May-Jun; 20(3):249-57.
Score: 0.107
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Detection of posteriorly located breast tumors using gold nanoparticles: a breast-mimicking phantom study. J Xray Sci Technol. 2014; 22(6):785-96.
Score: 0.105
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Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry. Acad Radiol. 2013 Dec; 20(12):1542-50.
Score: 0.105
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A Pilot Study to Assess the Performance of Phase-Sensitive Breast Tomosynthesis. Radiology. 2023 Feb; 306(2):e213198.
Score: 0.048
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A phase sensitive x-ray breast tomosynthesis system: Preliminary patient images with cancer lesions. Phys Med Biol. 2021 10 29; 66(21).
Score: 0.045
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Development and preclinical evaluation of a patient-specific high energy x-ray phase sensitive breast tomosynthesis system. Med Phys. 2021 May; 48(5):2511-2520.
Score: 0.043