Bin Zheng
Orcid: 0000-0002-7682-6648Affiliations:
- University of Oklahoma, School of Electrical and Computer Engineering, Norman, OK, USA
- University of Pittsburgh Medical Center, Department of Radiology, PA, USA (1993 - 2013)
- University of Delaware, Department of Electrical Engineering, Newark, DE, USA (PhD 1993)
According to our database1,
Bin Zheng
authored at least 126 papers
between 1998 and 2023.
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Bibliography
2023
Developing and assessing an AI-based multi-task prediction system to assist radiologists detecting lung diseases in reading chest x-ray images.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
An observer comparison study to evaluate a machine learning model to quantify the infected pneumonia on lung CT images.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
Deep learning-based rectum segmentation on low-field prostate MRI to assist image-guided biopsy.
Proceedings of the Medical Imaging 2023: Image-Guided Procedures, 2023
Improving medical image segmentation and classification using a novel joint deep learning model.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023
2022
C<sup>2</sup>MA-Net: Cross-Modal Cross-Attention Network for Acute Ischemic Stroke Lesion Segmentation Based on CT Perfusion Scans.
IEEE Trans. Biomed. Eng., 2022
Recent advances and clinical applications of deep learning in medical image analysis.
Medical Image Anal., 2022
Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms.
CoRR, 2022
CoRR, 2022
Assessment of a new CAD-generated imaging marker to predict risk of having mammography-occult tumors.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Comparison of performance in breast lesions classification using radiomics and deep transfer learning: an assessment study.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Developing interactive computer-aided detection tools to support translational clinical research.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Identifying an optimal machine learning generated image marker to predict survival of gastric cancer patients.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
Applying a novel two-stage deep-learning model to improve accuracy in detecting retinal fundus images.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
Fusion of handcrafted and deep transfer learning features to improve performance of breast lesion classification.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
Improving the performance of computer-aided classification of breast lesions using a new feature fusion method.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
2021
Applying a Random Projection Algorithm to Optimize Machine Learning Model for Breast Lesion Classification.
IEEE Trans. Biomed. Eng., 2021
Recent advances and clinical applications of deep learning in medical image analysis.
CoRR, 2021
Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images.
Comput. Methods Programs Biomed., 2021
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
Detecting COVID-19 infected pneumonia from x-ray images using a deep learning model with image preprocessing algorithm.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
Applying quantitative image markers to predict clinical measures after aneurysmal subarachnoid hemorrhage.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
An interactive computer-aided detection software tool for quantitative estimation of intracerebral hemorrhage.
Proceedings of the Medical Imaging 2021: Biomedical Applications in Molecular, 2021
2020
Development and Assessment of a New Global Mammographic Image Feature Analysis Scheme to Predict Likelihood of Malignant Cases.
IEEE Trans. Medical Imaging, 2020
Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms.
Int. J. Medical Informatics, 2020
A Stacked Generalization U-shape network based on zoom strategy and its application in biomedical image segmentation.
Comput. Methods Programs Biomed., 2020
Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients.
Comput. Methods Programs Biomed., 2020
A new interactive visual-aided decision-making supporting tool to predict severity of acute ischemic stroke.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020
2019
Developing global image feature analysis models to predict cancer risk and prognosis.
Vis. Comput. Ind. Biomed. Art, 2019
Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer.
Comput. Methods Programs Biomed., 2019
A robust method for segmenting pectoral muscle in mediolateral oblique (MLO) mammograms.
Int. J. Comput. Assist. Radiol. Surg., 2019
Assessment of a quantitative mammographic imaging marker for breast cancer risk prediction.
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Developing a new quantitative imaging marker to predict pathological complete response to neoadjuvant chemotherapy.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Design, fabrication and evaluation of non-imaging, label-free pre-screening tool using quantified bio-electrical tissue profile.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019
Developing a computer-aided image analysis and visualization tool to predict region-specific brain tissue "at risk" for developing acute ischemic stroke.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019
2018
Using Microbubble as Contrast Agent for High-Energy X-Ray In-line Phase Contrast Imaging: Demonstration and Comparison Study.
IEEE Trans. Biomed. Eng., 2018
A new near-term breast cancer risk prediction scheme based on the quantitative analysis of ipsilateral view mammograms.
Comput. Methods Programs Biomed., 2018
Comput. Medical Imaging Graph., 2018
A performance comparison of low- and high-level features learned by deep convolutional neural networks in epithelium and stroma classification.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Applying a new unequally weighted feature fusion method to improve CAD performance of classifying breast lesions.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Computer-aided classification of breast masses using contrast-enhanced digital mammograms.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Association between mammogram density and background parenchymal enhancement of breast MRI.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
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
Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.
Comput. Biol. Medicine, 2017
Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction.
Int. J. Comput. Assist. Radiol. Surg., 2017
Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Balance the nodule shape and surroundings: a new multichannel image based convolutional neural network scheme on lung nodule diagnosis.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Automated detection and quantification of residual brain tumor using an interactive computer-aided detection scheme.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Apply radiomics approach for early stage prognostic evaluation of ovarian cancer patients: a preliminary study.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Current source enhancements in Electrical Impedance Spectroscopy (EIS) to cancel unwanted capacitive effects.
Proceedings of the Medical Imaging 2017: Biomedical Applications in Molecular, 2017
2016
A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration.
IEEE Trans. Medical Imaging, 2016
Fusion of Quantitative Image and Genomic Biomarkers to Improve Prognosis Assessment of Early Stage Lung Cancer Patients.
IEEE Trans. Biomed. Eng., 2016
Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome.
BMC Medical Imaging, 2016
Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
A B-spline image registration based CAD scheme to evaluate drug treatment response of ovarian cancer patients.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Increasing cancer detection yield of breast MRI using a new CAD scheme of mammograms.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Computer-aided classification of mammographic masses using the deep learning technology: a preliminary study.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Computer-aided global breast MR image feature analysis for prediction of tumor response to chemotherapy: performance assessment.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Proceedings of the Breast Imaging, 2016
Proceedings of the Breast Imaging, 2016
2015
An automated approach to improve efficacy in detecting residual malignant cancer cell for facilitating prognostic assessment of leukemia: an initial study.
Proceedings of the Medical Imaging 2015: Digital Pathology, 2015
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Association of mammographic image feature change and an increasing risk trend of developing breast cancer: an assessment.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
A new breast cancer risk analysis approach using features extracted from multiple sub-regions on bilateral mammograms.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Exploring new quantitative CT image features to improve assessment of lung cancer prognosis.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Automated detection of breast tumor in MRI and comparison of kinetic features for assessing tumor response to chemotherapy.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
A new application of electrical impedance spectroscopy for measuring glucose metabolism: a phantom study.
Proceedings of the Medical Imaging 2015: Biomedical Applications in Molecular, 2015
A new computer-aided detection scheme based on assessment of local bilateral mammographic feature asymmetry - a preliminary evaluation.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015
2014
Computer-Aided Diagnosis of Breast DCE-MRI Images Using Bilateral Asymmetry of Contrast Enhancement Between Two Breasts.
J. Digit. Imaging, 2014
Prediction of near-term risk of developing breast cancer using computerized features from bilateral mammograms.
Comput. Medical Imaging Graph., 2014
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
Fusion of digital breast tomosynthesis images via wavelet synthesis for improved lesion conspicuity.
Proceedings of the Medical Imaging 2014: Image Processing, 2014
A new mass classification system derived from multiple features and a trained MLP model.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014
Using undiagnosed data to enhance computerized breast cancer analysis with a three stage data labeling method.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014
2013
Association between bilateral asymmetry of kinetic features computed from the DCE-MRI images and breast cancer.
Proceedings of the Medical Imaging 2013: Computer-Aided Diagnosis, 2013
2012
J. Digit. Imaging, 2012
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012
Improving performance of computer-aided detection of pulmonary embolisms by incorporating a new pulmonary vascular-tree segmentation algorithm.
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012
Improving CAD performance by fusion of the bilateral mammographic tissue asymmetry information.
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012
2011
A Multistage Approach to Improve Performance of Computer-Aided Detection of Pulmonary Embolisms Depicted on CT Images: Preliminary Investigation.
IEEE Trans. Biomed. Eng., 2011
Assessment of Performance and Reliability of Computer-Aided Detection Scheme Using Content-Based Image Retrieval Approach and Limited Reference Database.
J. Digit. Imaging, 2011
Computerized prediction of breast cancer risk: comparison between the global and local bilateral mammographic tissue asymmetry.
Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011
Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization.
Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011
2010
Computer-aided Detection: The Impact of Machine Learning Classifier and Image Feature Selection on Scheme Performance.
Int. J. Intell. Inf. Process., 2010
Proceedings of the Medical Imaging 2010: Computer-Aided Diagnosis, 2010
2009
IEEE Trans. Medical Imaging, 2009
A Computational Geometry Approach to Automated Pulmonary Fissure Segmentation in CT Examinations.
IEEE Trans. Medical Imaging, 2009
Automated classification of metaphase chromosomes: Optimization of an adaptive computerized scheme.
J. Biomed. Informatics, 2009
Pulmonary airways tree segmentation from CT examinations using adaptive volume of interest.
Proceedings of the Medical Imaging 2009: Image Processing, 2009
Proceedings of the Medical Imaging 2009: Visualization, 2009
Computer-aided detection of HER2 amplification status using FISH images: a preliminary study.
Proceedings of the Medical Imaging 2009: Computer-Aided Diagnosis, 2009
2008
Development and assessment of an integrated computer-aided detection scheme for digital microscopic images of metaphase chromosomes.
J. Electronic Imaging, 2008
Automated identification of analyzable metaphase chromosomes depicted on microscopic digital images.
J. Biomed. Informatics, 2008
A rule-based computer scheme for centromere identification and polarity assignment of metaphase chromosomes.
Comput. Methods Programs Biomed., 2008
Assessment of the relationship between lesion segmentation accuracy and computer-aided diagnosis scheme performance.
Proceedings of the Medical Imaging 2008: Computer-Aided Diagnosis, 2008
Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment.
Proceedings of the Medical Imaging 2008: Computer-Aided Diagnosis, 2008
2007
Mass margins spiculations: agreement between ratings by observers and a computer scheme.
Proceedings of the Medical Imaging 2007: Computer-Aided Diagnosis, 2007
Improvement of Visual Similarity of Similar Breast Masses Selected by Computer-Aided Diagnosis Schemes.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007
2006
Proceedings of the Medical Imaging 2006: Image Processing, 2006
2004
Automated detection and classification of interstitial lung diseases from low-dose CT images.
Proceedings of the Medical Imaging 2004: Image Processing, 2004
2003
Proceedings of the Medical Imaging 2003: Image Processing, 2003
Proceedings of the Medical Imaging 2003: Image Processing, 2003
2002
Incorporation of negative regions in a knowledge-based computer-aided detection scheme.
Proceedings of the Medical Imaging 2002: Image Processing, 2002
Change of region conspicuity in bilateral mammograms: potential impact on CAD performance.
Proceedings of the Medical Imaging 2002: Image Processing, 2002
2001
Proceedings of the Medical Imaging 2001: Image Processing, 2001
Correction of digitized mammograms to enhance soft display and tissue composition measurement.
Proceedings of the Medical Imaging 2001: Visualization, 2001
1999
Computer-assisted diagnosis of breast cancer using a data-driven Bayesian belief network.
Int. J. Medical Informatics, 1999
Application of a Bayesian belief network in a computer-assisted diagnosis scheme for mass detection.
Proceedings of the Medical Imaging 1999: Image Processing, 1999
Optimizing the feature set for a Bayesian network for breast cancer diagnosis using genetic algorithm techniques.
Proceedings of the Medical Imaging 1999: Image Processing, 1999
Proceedings of the Medical Imaging 1999: Image Processing, 1999
Proceedings of the Medical Imaging 1999: Image Processing, 1999
Comparison of artificial neural network and Bayesian belief network in a computer-assisted diagnosis scheme for mammography.
Proceedings of the International Joint Conference Neural Networks, 1999
Computer-aided diagnosis of breast cancer using artificial neural networks: comparison of backpropagation and genetic algorithms.
Proceedings of the International Joint Conference Neural Networks, 1999
1998
Assessment of mass detection using tissue background information as input to a computer-assisted diagnosis scheme.
Proceedings of the Medical Imaging 1998: Image Processing, 1998