Emily F. Conant

发表

Comparison of naïve Bayes and logistic regression for computer-aided diagnosis of breast masses using ultrasound imaging

Theodore W. Cary, Alyssa Cwanger, Santosh S. Venkatesh, 2012, Medical Imaging.

Diagnostic radiation dose after the implementation of digital breast tomosynthesis screening

Andrew D. A. Maidment, Bruno Barufaldi, Emily F. Conant, 2018, Other Conferences.

Observer performance evaluation of a method of simulating abnormalities in mammograms

Dev P. Chakraborty, Jeffrey P. Johnson, Emily F. Conant, 2002, SPIE Medical Imaging.

Breast tissue density quantification via digitized mammograms

Dev P. Chakraborty, Jayaram K. Udupa, Punam K. Saha, 2001, IEEE Transactions on Medical Imaging.

Deep-LIBRA: Artificial intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment pdf

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2020, ArXiv.

Quantitative description of solid breast nodules by ultrasound imaging

Emily F. Conant, Chandra M. Sehgal, Peter H. Arger, 2004, SPIE Medical Imaging.

Comparison of breast percent density estimation from raw versus processed digital mammograms

Emily F. Conant, Despina Kontos, Diane Li, 2011, Medical Imaging.

Fully automated chest wall line segmentation in breast MRI by using context information

Mitchell D. Schnall, Shandong Wu, Emily F. Conant, 2012, Medical Imaging.

Summary of Outcomes from Consecutive Years of Tomosynthesis Screening at an American Academic Institution

Mitchell D. Schnall, Andrew D. A. Maidment, Bruno Barufaldi, 2016, Digital Mammography / IWDM.

Application of computer-extracted breast tissue texture features in predicting false-positive recalls from screening mammography

Emily F. Conant, Jinbo Chen, Despina Kontos, 2014, Medical Imaging.

Breast density and parenchymal texture measures as potential risk factors for estrogen-receptor positive breast cancer

Emily F. Conant, Despina Kontos, Brad M. Keller, 2014, Medical Imaging.

Adaptive Multi-cluster Fuzzy C-Means Segmentation of Breast Parenchymal Tissue in Digital Mammography

Yan Wang, James C. Gee, Yuanjie Zheng, 2011, MICCAI.

Overview of Digital Breast Tomosynthesis

Emily F. Conant, 2018 .

Optical imaging as an adjunct to ultrasound in differentiating benign from malignant lesions

Britton Chance, Quing Zhu, Emily F. Conant, 1999, Photonics West - Biomedical Optics.

How to Write a Scientific Abstract for Symposium Submission

Emily F. Conant, Dianne Georgian-Smith, Margarita L. Zuley, 2019 .

A comparative analysis of 2D and 3D CAD for calcifications in digital breast tomosynthesis

Andrew D. A. Maidment, Emily F. Conant, Raymond J. Acciavatti, 2015, Medical Imaging.

Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

Emily F. Conant, Despina Kontos, Elizabeth S. McDonald, 2016, Radiology.

Associations between mammographic phenotypes and histopathologic features in ductal carcinoma in situ

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2019, Medical Imaging.

Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2017, Medical Imaging.

Temporal Subtraction Versus Dual-Energy Contrast-Enhanced Digital Breast Tomosynthesis: A Pilot Study

Ann-Katherine Carton, Andrew D. A. Maidment, Emily F. Conant, 2008, Digital Mammography / IWDM.

Interpreting the ROC curve from the radiologist's point of view: the diagnostician operating choice (DOC) curve

Elizabeth A. Krupinski, Emily F. Conant, Harold L. Kundel, 2005, SPIE Medical Imaging.

Volumetric versus area-based density assessment: comparisons using automated quantitative measurements from a large screening cohort

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2018, Medical Imaging.

A fully-automated software pipeline for integrating breast density and parenchymal texture analysis for digital mammograms: parameter optimization in a case-control breast cancer risk assessment study

Yan Wang, James C. Gee, Yuanjie Zheng, 2013, Medical Imaging.

Fully-automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI by integrating a continuous max-flow model and a likelihood atlas

Shandong Wu, Emily F. Conant, Despina Kontos, 2013, Medical Imaging.

Model-based estimation of breast percent density in raw and processed full-field digital mammography images from image-acquisition physics and patient-image characteristics

Emily F. Conant, Despina Kontos, Brad M. Keller, 2012, Medical Imaging.

Mammographic Parenchymal Texture Analysis for Estrogen-Receptor Subtype Specific Breast Cancer Risk Estimation

Mads Nielsen, Emily F. Conant, Despina Kontos, 2012, Digital Mammography / IWDM.

Fully-Automated Fibroglandular Tissue Segmentation in Breast MRI

Shandong Wu, Emily F. Conant, Despina Kontos, 2012, Digital Mammography / IWDM.

Digital Breast Tomosynthesis Parenchymal Texture Analysis for Breast Cancer Risk Estimation: A Preliminary Study

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2008, Digital Mammography / IWDM.

Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

Emily F. Conant, Jinbo Chen, Despina Kontos, 2016, SPIE Medical Imaging.

Artificial neural network to aid differentiation of malignant and benign breast masses by ultrasound imaging

Santosh S. Venkatesh, Emily F. Conant, Chandra M. Sehgal, 2005, SPIE Medical Imaging.

Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis.

Emily F. Conant, Sergei V. Fotin, Senthil Periaswamy, 2019, Radiology. Artificial intelligence.

Breast Cancer Risk Prediction via Area and Volumetric Estimates of Breast Density

Emily F. Conant, Despina Kontos, Brad M. Keller, 2012, Digital Mammography / IWDM.

Optimization of Contrast-Enhanced Digital Breast Tomosynthesis

Ann-Katherine Carton, Jingjing Li, Andrew D. A. Maidment, 2006, Digital Mammography / IWDM.

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

Andrew D. A. Maidment, Emily F. Conant, Despina Kontos, 2011, Medical Imaging.

A Comparative Study of the Inter-reader Variability of Breast Percent Density Estimation in Digital Mammography: Potential Effect of Reader's Training and Clinical Experience

Ann-Katherine Carton, Andrew D. A. Maidment, Cuiping Zhang, 2010, Digital Mammography / IWDM.

A superpixel-based framework for automatic tumor segmentation on breast DCE-MRI

Bilwaj Gaonkar, Christos Davatzikos, Jia Wu, 2015, Medical Imaging.

Robust radiomic feature selection in digital mammography: understanding the effect of imaging acquisition physics using phantom and clinical data analysis

Andrew D. A. Maidment, Emily F. Conant, Karla Kerlikowske, 2020, Medical Imaging.

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2010, Medical Imaging.

Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration

Christos Davatzikos, Jia Wu, Mark Rosen, 2015, Medical Imaging.

Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2016, SPIE Medical Imaging.

Validation and optimization of digital breast tomosynthesis reconstruction using an anthropomorphic software breast phantom

Ann-Katherine Carton, Andrew D. A. Maidment, Predrag R. Bakic, 2010, Medical Imaging.

Three-Dimensional Visualization of Breast Cancer

Andrew D. A. Maidment, Emily F. Conant, Michael Albert, 1998, Digital Mammography / IWDM.

A Comparative Study of Volumetric and Area-Based Breast Density Estimation in Digital Mammography: Results from a Screening Population

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2010, Digital Mammography / IWDM.

Mammographic phenotypes of breast cancer risk driven by breast anatomy

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2017, Medical Imaging.

Deep-LIBRA: Artificial intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2020, Medical Image Anal..

Radiologists’ Preferences for Digital Mammographic Display

Robert M. Nishikawa, Bradley M. Hemminger, Stephen R. Aylward, 2000 .

Observer Variability in BI-RADS Ultrasound Features and Its Influence on Computer-Aided Diagnosis of Breast Masses

Emily F. Conant, Chandra M. Sehgal, Ghizlane Bouzghar, 2015, Advances in breast cancer research.

Near-automatic quantification of breast tissue glandularity via digitized mammograms

Jayaram K. Udupa, Punam K. Saha, Emily F. Conant, 1999, Medical Imaging.

Rapid and Sensitive Optical Imaging of Tissue Functional Activity, and Breast

Shoko Nioka, Britton Chance, Emily F. Conant, 1998 .

Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment.

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2011, Radiology.

Incremental impact of breast cancer SNP panel on risk classification in a screening population of white and African American women

Anne Marie McCarthy, Emily F. Conant, Susan M. Domchek, 2013, Breast Cancer Research and Treatment.

Determining the optimal angular range of the X-ray source motion in tomosynthesis using virtual clinical trials

Andrew D. A. Maidment, Predrag R. Bakic, Bruno Barufaldi, 2020 .

Racial Differences in Quantitative Measures of Area and Volumetric Breast Density.

Anne Marie McCarthy, Emily F. Conant, Despina Kontos, 2016, Journal of the National Cancer Institute.

Association of Digital Breast Tomosynthesis vs Digital Mammography With Cancer Detection and Recall Rates by Age and Breast Density

Natasha K. Stout, Donald L. Weaver, Emily F. Conant, 2019, JAMA oncology.