Computer-aided detection system for clustered microcalcifications in digital breast tomosynthesis using joint information from volumetric and planar projection images
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Heang-Ping Chan | Ravi K. Samala | Jun Wei | Yao Lu | Lubomir M Hadjiiski | Mark A Helvie | Ravi K Samala | H. Chan | M. Helvie | L. Hadjiiski | Jun Wei | Yao Lu
[1] Lubomir M. Hadjiiski,et al. Image quality of microcalcifications in digital breast tomosynthesis: effects of projection-view distributions. , 2011, Medical physics.
[2] Lubomir M. Hadjiiski,et al. Selective-diffusion regularization for enhancement of microcalcifications in digital breast tomosynthesis reconstruction. , 2010, Medical physics.
[3] Nico Karssemeijer,et al. Correlating locations in ipsilateral breast tomosynthesis views using an analytical hemispherical compression model. , 2011, Physics in medicine and biology.
[4] I. Sechopoulos. A review of breast tomosynthesis. Part I. The image acquisition process. , 2013, Medical physics.
[5] Lubomir M. Hadjiiski,et al. Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis. , 2014, Medical physics.
[6] R A Schmidt,et al. Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: a preliminary study. , 2008, Medical physics.
[7] Simon R. Arridge,et al. Adaptive diffusion regularization method of inverse problem for diffuse optical tomography , 2005, European Conference on Biomedical Optics.
[8] R. Taschereau,et al. Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures , 2010, Nucleic acids research.
[9] S. Ciatto,et al. Integration of 3D digital mammography with tomosynthesis for population breast-cancer screening (STORM): a prospective comparison study. , 2013, The Lancet. Oncology.
[10] Riham Eiada,et al. Evaluation of breast amorphous calcifications by a computer-aided detection system in full-field digital mammography. , 2012, The British journal of radiology.
[11] Lubomir M. Hadjiiski,et al. Digital breast tomosynthesis: effects of projection-view distribution on computer-aided detection of microcalcification clusters , 2014, Medical Imaging.
[12] Andriy I. Bandos,et al. Prospective trial comparing full-field digital mammography (FFDM) versus combined FFDM and tomosynthesis in a population-based screening programme using independent double reading with arbitration , 2013, European Radiology.
[13] Dev P Chakraborty,et al. Observer studies involving detection and localization: modeling, analysis, and validation. , 2004, Medical physics.
[14] Serge Muller,et al. Computer-Aided Microcalcification Detection on Digital Breast Tomosynthesis Data: A Preliminary Evaluation , 2008, Digital Mammography / IWDM.
[15] N. Petrick,et al. Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces. , 1998, Medical physics.
[16] Berkman Sahiner,et al. Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach. , 2011, Medical physics.
[17] Daniel F Heitjan,et al. Screening outcomes following implementation of digital breast tomosynthesis in a general-population screening program. , 2014, Journal of the National Cancer Institute.
[18] David Gur,et al. Digital breast tomosynthesis: observer performance study. , 2009, AJR. American journal of roentgenology.
[19] Lubomir M. Hadjiiski,et al. Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection images , 2014, Physics in medicine and biology.
[20] Berkman Sahiner,et al. Computer aided detection of clusters of microcalcifications on full field digital mammograms. , 2006, Medical physics.
[21] Nico Karssemeijer,et al. Generating Synthetic Mammograms From Reconstructed Tomosynthesis Volumes , 2013, IEEE Transactions on Medical Imaging.
[22] Chuan Zhou,et al. Multichannel response analysis on 2D projection views for detection of clustered microcalcifications in digital breast tomosynthesis. , 2014, Medical physics.
[23] Luisa P. Wallace,et al. Multiview-based computer-aided detection scheme for breast masses. , 2006, Medical physics.
[24] Nico Karssemeijer,et al. Combining two mammographic projections in a computer aided mass detection method. , 2007, Medical physics.
[25] Lubomir M. Hadjiiski,et al. Effect of finite sample size on feature selection and classification: a simulation study. , 2010, Medical physics.
[26] C. Metz,et al. "Proper" Binormal ROC Curves: Theory and Maximum-Likelihood Estimation. , 1999, Journal of mathematical psychology.
[27] Ning Xu,et al. False positive reduction of microcalcification cluster detection in digital breast tomosynthesis , 2014, Medical Imaging.
[28] H P Chan,et al. Selection of an optimal neural network architecture for computer-aided detection of microcalcifications--comparison of automated optimization techniques. , 2001, Medical physics.
[29] Berkman Sahiner,et al. Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume. , 2014, Medical physics.
[30] Tor D Tosteson,et al. Digital breast tomosynthesis: initial experience in 98 women with abnormal digital screening mammography. , 2007, AJR. American journal of roentgenology.
[31] Berkman Sahiner,et al. Optimal neural network architecture selection: improvement in computerized detection of microcalcifications. , 2002, Academic radiology.
[32] David Gur,et al. Detection and classification of calcifications on digital breast tomosynthesis and 2D digital mammography: a comparison. , 2011, AJR. American journal of roentgenology.
[33] David Gur,et al. Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment , 2008, SPIE Medical Imaging.
[34] Berkman Sahiner,et al. Joint two-view information for computerized detection of microcalcifications on mammograms. , 2006, Medical physics.
[35] Heang-Ping Chan,et al. Digital breast tomosynthesis: observer performance of clustered microcalcification detection on breast phantom images acquired with an experimental system using variable scan angles, angular increments, and number of projection views. , 2014, Radiology.
[36] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[37] Heang-Ping Chan,et al. Analysis of computer-aided detection techniques and signal characteristics for clustered microcalcifications on digital mammography and digital breast tomosynthesis , 2016, Physics in medicine and biology.
[38] Nico Karssemeijer,et al. Learning from unbalanced data: A cascade-based approach for detecting clustered microcalcifications , 2014, Medical Image Anal..
[39] Berkman Sahiner,et al. Computer-aided detection system for clustered microcalcifications: comparison of performance on full-field digital mammograms and digitized screen-film mammograms , 2007, Physics in medicine and biology.
[40] Lubomir M. Hadjiiski,et al. A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis. , 2006, Medical physics.
[41] Andriy I. Bandos,et al. Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program. , 2013, Radiology.
[42] Jeffrey A. Fessler,et al. Adaptive diffusion regularization for enhancement of microcalcifications in digital breast tomosynthesis (DBT) reconstruction , 2011, Medical Imaging.
[43] Ian H. Witten,et al. The WEKA data mining software: an update , 2009, SKDD.
[44] Nico Karssemeijer,et al. Noise model for microcalcification detection in reconstructed tomosynthesis slices , 2009, Medical Imaging.