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Publications

Found 327 results
2017
Revealing cancer subtypes with higher-order correlations applied to imaging and omics data, Graim, K., Liu T. T., Achrol A. S., Paull E. O., Newton Y., Chang S. D., Harsh G. R. th, Cordero S. P., Rubin D. L., and Stuart J. M. , BMC Med Genomics, Mar 31, Volume 10, Number 1, p.20, (2017)
Robust noise region-based active contour model via local similarity factor for image segmentation, Niu, S. J., Chen Q., de Sisternes L., Ji Z. X., Zhou Z. M., and Rubin D. L. , Pattern RecognitionPattern Recognition, Jan, Volume 61, p.104-119, (2017)
Software for Distributed Computation on Medical Databases: A Demonstration Project, Narasimhan, Balasubramanian, Rubin Daniel L., Gross Samuel M., Bendersky Marina, and Lavori Philip W. , Journal of Statistical Software, 2017-05-03, Volume 77, Number 13, p.22, (2017)
Toward Automated Pre-Biopsy Thyroid Cancer Risk Estimation in Ultrasound, Galimzianova, A., Siebert S. M., Kamaya A., Desser T. S., and Rubin D. L. , AMIA Annu Symp Proc, Volume 2017, p.734-741, (2017)
Transfer learning on fused multiparametric MR images for classifying histopathological subtypes of rhabdomyosarcoma, Banerjee, I., Crawley A., Bhethanabotla M., Daldrup-Link H. E., and Rubin D. L. , Comput Med Imaging Graph, May 05, (2017)
Use of Radiology Procedure Codes in Health Care: The Need for Standardization and Structure, Wang, K. C., Patel J. B., Vyas B., Toland M., Collins B., Vreeman D. J., Abhyankar S., Siegel E. L., Rubin D. L., and Langlotz C. P. , Radiographics, Jul-Aug, Volume 37, Number 4, p.1099-1110, (2017)
Volumetric Image Registration From Invariant Keypoints, Rister, B., Horowitz M. A., and Rubin D. L. , IEEE Trans Image Process, Oct, Volume 26, Number 10, p.4900-4910, (2017)
2016
A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT, Cirujeda, P., Y. Cid Dicente, Muller H., Rubin D., Aguilera T. A., Loo B. W., Diehn M., Binefa X., and Depeursinge A. , IEEE Trans Med Imaging, Dec, Volume 35, Number 12, p.2620-2630, (2016)
Analysis of Inner and Outer Retinal Thickness in Patients Using Hydroxychloroquine Prior to Development of Retinopathy, de Sisternes, L., Hu J., Rubin D. L., and Marmor M. F. , JAMA Ophthalmol, Mar 17, (2016)
Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles, Barker, J., Hoogi A., Depeursinge A., and Rubin D. L. , Med Image Anal, May, Volume 30, p.60-71, (2016)
Automated geographic atrophy segmentation for SD-OCT images using region-based C-V model via local similarity factor, Niu, S., de Sisternes L., Chen Q., Leng T., and Rubin D. L. , Biomed Opt Express, Feb 1, Volume 7, Number 2, p.581-600, (2016)
Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS, Jeffers, A. M., Sieh W., Lipson J. A., Rothstein J. H., McGuire V., Whittemore A. S., and Rubin D. L. , Radiology, Sep 5, p.152062, (2016)
Building and Querying RDF/OWL Database of Semantically Annotated Nuclear Medicine Images, Hwang, K. H., Lee H., Koh G., Willrett D., and Rubin D. L. , J Digit Imaging, Oct 26, (2016)
Case-control study of mammographic density and breast cancer risk using processed digital mammograms, Habel, L. A., Lipson J. A., Achacoso N., Rothstein J. H., Yaffe M. J., Liang R. Y., Acton L., McGuire V., Whittemore A. S., Rubin D. L., et al. , Breast Cancer Res, Volume 18, Number 1, p.53, (2016)
A combinatorial radiographic phenotype may stratify patient survival and be associated with invasion and proliferation characteristics in glioblastoma, Rao, A., Rao G., Gutman D. A., Flanders A. E., Hwang S. N., Rubin D. L., Colen R. R., Zinn P. O., Jain R., Wintermark M., et al. , J Neurosurg, Apr, Volume 124, Number 4, p.1008-17, (2016)
Common Data Elements in Radiology, Rubin, D. L., and Kahn, Jr. C. E. , Radiology, Nov 10, p.161553, (2016)
Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas, Liu, T. T., Achrol A. S., Mitchell L. A., Du W. A., Loya J. J., Rodriguez S. A., Feroze A., Westbroek E. M., Yeom K. W., Stuart J. M., et al. , AJNR Am J Neuroradiol, Apr, Volume 37, Number 4, p.621-8, (2016)
A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound, Lekadir, K., Galimzianova A., Betriu A., Vila M. D., Igual L., Rubin D., Fernandez E., Radeva P., and Napel S. , IEEE J Biomed Health Inform, Nov 22, (2016)
Early-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of 18F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis, Wu, J., Aguilera T., Shultz D., Gudur M., Rubin D. L., Loo, Jr. B. W., Diehn M., and Li R. , Radiology, Apr 5, p.151829, (2016)
Early-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of (18)F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis, Wu, J., Aguilera T., Shultz D., Gudur M., Rubin D. L., Loo, Jr. B. W., Diehn M., and Li R. , Radiology, Oct, Volume 281, Number 1, p.270-8, (2016)
Fully Automated Prediction of Geographic Atrophy Growth Using Quantitative Spectral-Domain Optical Coherence Tomography Biomarkers, Niu, S., de Sisternes L., Chen Q., Rubin D. L., and Leng T. , Ophthalmology, Aug, Volume 123, Number 8, p.1737-50, (2016)
Intratumor Partitioning of Serial Computed Tomography and FDG Positron Emission Tomography Images Identifies High-Risk Tumor Subregions and Predicts Patterns of Failure in Non-Small Cell Lung Cancer After Radiation Therapy, Wu, J., Gensheimer M. F., Dong X., Rubin D. L., Napel S., Diehn M., Loo, Jr. B. W., and Li R. , Int J Radiat Oncol Biol Phys, Oct 1, Volume 96, Number 2S, p.S100, (2016)
Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment, Liu, T. T., Achrol A. S., Mitchell L. A., Rodriguez S. A., Feroze A.,, Kim C., Chaudhary N., Gevaert O., Stuart J. M., et al. , Neuro Oncol, Dec 22, (2016)
A method for normalizing pathology images to improve feature extraction for quantitative pathology, Tam, A., Barker J., and Rubin D. , Med Phys, Jan, Volume 43, Number 1, p.528, (2016)
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features, Yu, K. H., Zhang C., Berry G. J., Altman R. B., Re C., Rubin D. L., and Snyder M. , Nat Commun, Volume 7, p.12474, (2016)
Quantitative Imaging in Cancer Clinical Trials, Yankeelov, T. E., Mankoff D. A., Schwartz L. H., Lieberman F. S., Buatti J. M., Mountz J. M., Erickson B. J., Fennessy F. M., Huang W., Kalpathy-Cramer J., et al. , Clin Cancer Res, Jan 15, Volume 22, Number 2, p.284-90, (2016)
Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study, Wu, J., Gensheimer M. F., Dong X., Rubin D. L., Napel S., Diehn M., Loo, Jr. B. W., and Li R. , Int J Radiat Oncol Biol Phys, Aug 1, Volume 95, Number 5, p.1504-12, (2016)
Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data, Finlayson, S. G., Levy M., Reddy S., and Rubin D. L. , J Biomed Inform, Apr, Volume 60, p.104-13, (2016)
Using automatically extracted information from mammography reports for decision-support, Bozkurt, S., Gimenez F., Burnside E. S., Gulkesen K. H., and Rubin D. L. , J Biomed Inform, Aug, Volume 62, p.224-31, (2016)
2015
3D Markup of Radiological Images in ePAD, a Web-Based Image Annotation Tool, Moreira, D. A., Hage C., Luque E. F., Willrett D., and Rubin D. L. , Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on, 22-25 June 2015, p.97-102, (2015)
3D Riesz-wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT, Cirujeda, P., Muller H., Rubin D., Aguilera T. A., Loo B. W., Diehn M., Binefa X., and Depeursinge A. , Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, 25-29 Aug. 2015, p.7909-7912, (2015)
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients, Nicolasjilwan, M., Hu Y., Yan C., Meerzaman D., Holder C. A., Gutman D., Jain R., Colen R., Rubin D. L., Zinn P. O., et al. , J Neuroradiol, Jul, Volume 42, Number 4, p.212-21, (2015)
Application of improved homogeneity similarity-based denoising in optical coherence tomography retinal images, Chen, Q., de Sisternes L., Leng T., and Rubin D. L. , J Digit Imaging, Jun, Volume 28, Number 3, p.346-61, (2015)
Automated Classification of Usual Interstitial Pneumonia Using Regional Volumetric Texture Analysis in High-Resolution Computed Tomography, Depeursinge, A., Chin A. S., Leung A. N., Terrone D., Bristow M., Rosen G., and Rubin D. L. , Invest Radiol, Apr, Volume 50, Number 4, p.261-267, (2015)
Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A Modular Approach with Ensemble of Convolutional Neural Networks, Ertosun, M. G., and Rubin D. L. , Proceedings of the American Medical Informatics Association, p.1899-1908, (2015)
Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection, Wu, Menglin, Leng Theodore, de Sisternes Luis, Rubin Daniel L., and Chen Qiang , Optics ExpressOptics Express, 2015/11/30, Volume 23, Number 24, p.31216-31229, (2015)
Automatic Classification of Cancer Tumors Using Image Annotations and Ontologies, Luque, E. F., Rubin D. L., and Moreira D. A. , Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on, 22-25 June 2015, p.368-369, (2015)
Content-based image retrieval in radiology: analysis of variability in human perception of similarity, Faruque, J., Beaulieu C. F., Rosenberg J., Rubin D. L., Yao D., and Napel S. , J Med Imaging (Bellingham), Apr, Volume 2, Number 2, p.025501, (2015)
Improved patch based automated liver lesion classification by separate analysis of the interior and boundary regions, Diamant, I., Hoogi A., Beaulieu C., Safdari M., Klang E., Amitai M., Greenspan H., and Rubin D. , IEEE J Biomed Health Inform, Sep 11, (2015)
Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea, de Sisternes, L., Hu J., Rubin D. L., and Marmor M. F. , Invest Ophthalmol Vis Sci, May, Volume 56, Number 5, p.3415-26, (2015)
Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities, Itakura, H., Achrol A. S., Mitchell L. A., Loya J. J., Liu T., Westbroek E. M., Feroze A. H., Rodriguez S., Echegaray S., Azad T. D., et al. , Sci Transl Med, Sep 2, Volume 7, Number 303, p.303ra138, (2015)
Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival, Wangaryattawanich, P., Hatami M., Wang J., Thomas G., Flanders A., Kirby J., Wintermark M., Huang E. S., Bakhtiari A. S., Luedi M. M., et al. , Neuro Oncol, Jul 22, (2015)
Ontology-based Image Navigation: Exploring 3.0-T MR Neurography of the Brachial Plexus Using AIM and RadLex, Wang, K. C., Salunkhe A. R., Morrison J. J., Lee P. P., Mejino J. L., Detwiler L. T., Brinkley J. F., Siegel E. L., Rubin D. L., and Carrino J. A. , Radiographics, Jan-Feb, Volume 35, Number 1, p.142-51, (2015)
Optimized steerable wavelets for texture analysis of lung tissue in 3-D CT: Classification of usual interstitial pneumonia, Depeursinge, A., Pad P., Chin A. S., Leung A. N., Rubin D. L., Muller H., and Unser M. , Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, 16-19 April 2015, p.403-406, (2015)
Polychromatic X-Ray Absorptiometry to Quantify Breast Density Volume, Ratio and their Associated Breast Cancer Risk in Full-Digital Mammography, de Sisternes, L., Rothstein J. H., Jeffers A. M., Sieh W., and Rubin D. L. , Proceedings of the American Medical Informatics Association, p.28-29, (2015)
Probabilistic visual search for masses within mammography images using deep learning, Ertosun, M. G., and Rubin D. L. , 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 9-12 Nov. 2015, Washington, DC, p.1310-1315, (2015)
Radiogenomics of clear cell renal cell carcinoma: preliminary findings of The Cancer Genome Atlas-Renal Cell Carcinoma (TCGA-RCC) Imaging Research Group, Shinagare, A. B., Vikram R., Jaffe C., Akin O., Kirby J., Huang E., Freymann J., Sainani N. I., Sadow C. A., Bathala T. K., et al. , Abdom Imaging, Mar 10, (2015)
Restricted Summed-Area Projection for Geographic Atrophy Visualization in SD-OCT Images, Chen, Q., Niu S., Shen H., Leng T., de Sisternes L., and Rubin D. L. , Transl Vis Sci Technol, Sep, Volume 4, Number 5, p.2, (2015)
Semantic Retrieval of Radiological Images with Relevance Feedback, Kurtz, Camille, Idoux Paul-André, Thangali Avinash, Cloppet Florence, Beaulieu Christopher F., and Rubin Daniel L. , Cham, p.11-25, (2015)
Visual Prognosis of Eyes Recovering From Macular Hole Surgery Through Automated Quantitative Analysis of Spectral-Domain Optical Coherence Tomography (SD-OCT) Scans, de Sisternes, L., Hu J., Rubin D. L., and Leng T. , Invest Ophthalmol Vis Sci, Jul, Volume 56, Number 8, p.4631-43, (2015)
Weighted locality-constrained linear coding for lesion classification in CT images, Yixuan, Yuan, Hoogi A., Beaulieu C. F., Meng M. Q. H., and Rubin D. L. , Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, 25-29 Aug. 2015, p.6362-6365, (2015)
2014
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients, Nicolasjilwan, M., Hu Y., Yan C., Meerzaman D., Holder C. A., Gutman D., Jain R., Colen R., Rubin D. L., Zinn P. O., et al. , J NeuroradiolJ Neuroradiol, Jul 2, (2014)
Automated Classification of Usual Interstitial Pneumonia Using Regional Volumetric Texture Analysis in High-Resolution Computed Tomography, Depeursinge, A., Chin A. S., Leung A. N., Terrone D., Bristow M., Rosen G., and Rubin D. L. , Invest Radiol, Dec 30, (2014)
Automated detection of ambiguity in BI-RADS assessment categories in mammography reports, Bozkurt, S., and Rubin D. , Stud Health Technol Inform, Volume 197, p.35-9, (2014)
Automated retinal layers segmentation in SD-OCT images using dual-gradient and spatial correlation smoothness constraint, Niu, S., Chen Q., de Sisternes L., Rubin D. L., Zhang W., and Liu Q. , Comput Biol MedComput Biol Med, Sep 6, Volume 54C, p.116-128, (2014)
Automated tracking of quantitative assessments of tumor burden in clinical trials, Rubin, D. L., Willrett D., O'Connor M. J., Hage C., Kurtz C., and Moreira D. A. , Transl OncolTransl Oncol, Feb, Volume 7, Number 1, p.23-35, (2014)
Automatic abstraction of imaging observations with their characteristics from mammography reports, Bozkurt, S., Lipson J. A., Senol U., and Rubin D. L. , J Am Med Inform Assoc, Oct 28, (2014)
Classification of hepatic lesions using the matching metric, Adcock, Aaron, Rubin Daniel, and Carlsson Gunnar , Computer Vision and Image Understanding, 4//, Volume 121, p.36-42, (2014)
On combining image-based and ontological semantic dissimilarities for medical image retrieval applications, Kurtz, C., Depeursinge A., Napel S., Beaulieu C. F., and Rubin D. L. , Med Image AnalMed Image Anal, Oct, Volume 18, Number 7, p.1082-100, (2014)
Developing a comprehensive database management system for organization and evaluation of mammography datasets, Wu, Y., Rubin D. L., Woods R. W., Elezaby M., and Burnside E. S. , Cancer InformCancer Inform, Volume 13, Number Suppl 3, p.53-62, (2014)
Errors in Quantitative Image Analysis due to Platform-Dependent Image Scaling, Chenevert, T. L., Malyarenko D. I., Newitt D., Li X., Jayatilake M., Tudorica A., Fedorov A., Kikinis R., Liu T. T., Muzi M., et al. , Transl OncolTransl Oncol, Feb, Volume 7, Number 1, p.65-71, (2014)
Extracting imaging observation entities in mammography reports, Bozkurt, S., and Rubin D. , Stud Health Technol Inform, Volume 205, p.1223, (2014)
A False Color Fusion Strategy for Drusen and Geographic Atrophy Visualization in Optical Coherence Tomography Images, Chen, Q., Leng T., Niu S., Shi J., de Sisternes L., and Rubin D. L. , RetinaRetina, Jul 24, (2014)
A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations, Kurtz, C., Beaulieu C. F., Napel S., and Rubin D. L. , J Biomed Inform, Mar 12, (2014)
Letter to Cancer Center Directors: Progress in Quantitative Imaging As a Means to Predict and/or Measure Tumor Response in Cancer Therapy Trials, Mountz, J. M., Yankeelov T. E., Rubin D. L., Buatti J. M., Erikson B. J., Fennessy F. M., Gillies R. J., Huang W., Jacobs M. A., Kinahan P. E., et al. , J Clin OncolJ Clin Oncol, May 27, (2014)
Neuroanatomical domain of the foundational model of anatomy ontology, Nichols, B. N., Mejino J. L., Detwiler L. T., Nilsen T. T., Martone M. E., Turner J. A., Rubin D. L., and Brinkley J. F. , J Biomed SemanticsJ Biomed Semantics, Jan 8, Volume 5, Number 1, p.1, (2014)
A Novel Method to Assess Incompleteness of Mammography Report Content (Martin Epstein Award), Gimenez, F., Wu Y., Burnside E. S., and Rubin D. L. , Proceedings of the American Medical Informatics Association, Washington, DC, p.1758-1767, (2014)
Predicting Visual Semantic Descriptive Terms From Radiological Image Data: Preliminary Results With Liver Lesions in CT, Depeursinge, A., Kurtz C., Beaulieu C., Napel S., and Rubin D. , IEEE Trans Med ImagingIEEE Trans Med Imaging, Aug, Volume 33, Number 8, p.1669-76, (2014)
Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression, de Sisternes, L., Simon N., Tibshirani R., Leng T., and Rubin D. L. , Invest Ophthalmol Vis SciInvest Ophthalmol Vis Sci, Nov, Volume 55, Number 11, p.7093-103, (2014)
Registration of SD-OCT en-face images with color fundus photographs based on local patch matching, Niu, S., Chen Q., Shen H., de Sisternes L., and Rubin D. L. , Ophthalmic Medical Image Analysis First International Workshop, OMIA 2014 in Conjunction with MICCAI 2014, Boston, Massachusetts, (2014)
A robust classifier to distinguish noise from FMRI independent components, Sochat, V., Supekar K., Bustillo J., Calhoun V., Turner J. A., and Rubin D. L. , PLoS ONEPLoS ONE, Volume 9, Number 4, p.e95493, (2014)
Semiautomatic segmentation and follow-up of multicomponent low-grade tumors in longitudinal brain MRI studies, Weizman, L., Sira L. B., Joskowicz L., Rubin D. L., Yeom K. W., Constantini S., Shofty B., and Bashat D. B. , Med PhysMed Phys, May, Volume 41, Number 5, p.052303, (2014)
Utilisation de relations ontologiques pour la comparaison d'images décrites par des annotations sémantiques, Kurtz, C., and Rubin D. L. , EGC 2014, Conférence Francophone sur l'Extraction et la Gestion de Connaissance, Rennes, France, January 2014, (2014)
2013
ACR-AAPM-SIIM practice guideline for determinants of image quality in digital mammography, Kanal, K. M., Krupinski E., Berns E. A., Geiser W. R., Karellas A., Mainiero M. B., Martin M. C., Patel S. B., Rubin D. L., Shepard J. D., et al. , J Digit ImagingJournal of Digital Imaging, Feb, Volume 26, Number 1, p.10-25, (2013)
Annotation for information extraction from mammography reports, Bozkurt, S., Gulkesen K. H., and Rubin D. , Stud Health Technol Inform, Volume 190, p.183-5, (2013)
Automated drusen segmentation and quantification in SD-OCT images, Chen, Q., Leng T., Zheng L., Kutzscher L., Ma J., de Sisternes L., and Rubin D. L. , Med Image AnalMed Image Anal, Jul 2, Volume 17, Number 8, p.1058-1072, (2013)
A Combinatorial Radiophenotype Stratifies Patient Survival and Associates with Invasion/Proliferation Characteristics in Glioblastoma (Gbm), Rao, A., Rao G., Flanders A., and Grp TCGA Glioma Phe , Neuro-OncologyNeuro-Oncology, Nov, Volume 15, p.202-202, (2013)
Comprehensive molecular characterization of clear cell renal cell carcinoma, Research, Network Cancer Gen , NatureNature, Jul 4, Volume 499, Number 7456, p.43-9, (2013)
Dynamic contrast-enhanced MRI-based biomarkers of therapeutic response in triple-negative breast cancer, Golden, D. I., Lipson J. A., Telli M. L., Ford J. M., and Rubin D. L. , J Am Med Inform Assoc, Nov 1, Volume 20, Number 6, p.1059-66, (2013)
Formative Evaluation of Ontology Learning Methods for Entity Discovery by Using Existing Ontologies as Reference Standards, Liu, K., Mitchell K. J., Chapman W. W., Savova G. K., Sioutos N., Rubin D. L., and Crowley R. S. , Methods Inf MedMethods Inf Med, May 13, Volume 52, Number 4, (2013)
Imaging informatics: essential tools for the delivery of imaging services, Mendelson, D. S., and Rubin D. L. , Acad Radiol, Oct, Volume 20, Number 10, p.1195-212, (2013)
An Improved Optical Coherence Tomography-Derived Fundus Projection Image for Drusen Visualization, Chen, Q., Leng T., Zheng L. L., Kutzscher L., de Sisternes L., and Rubin D. L. , RetinaRetina, Oct 30, (2013)
MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set, Gutman, D. A., Cooper L. A., Hwang S. N., Holder C. A., Gao J., Aurora T. D., Dunn, Jr. W. D., Scarpace L., Mikkelsen T., Jain R., et al. , RadiologyRadiology, May, Volume 267, Number 2, p.560-569, (2013)
A picture is worth a thousand words: needs assessment for multimedia radiology reports in a large tertiary care medical center, Nayak, L., Beaulieu C. F., Rubin D. L., and Lipson J. A. , Acad Radiol, Dec, Volume 20, Number 12, p.1577-83, (2013)
Qualitative and quantitative image-based biomarkers of therapeutic response in triple-negative breast cancer, Golden, D. I., Lipson J. A., Telli M. L., Ford J. M., and Rubin D. L. , AMIA Summits Transl Sci ProcAMIA Summits Transl Sci Proc, Volume 2013, p.62, (2013)
Quantitative evaluation of drusen on photographs, Rubin, D. L., de Sisternes L., Kutzscher L., Chen Q., Leng T., and Zheng L. L. , OphthalmologyOphthalmology, Mar, Volume 120, Number 3, p.644-644 e2, (2013)
Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers, Buckler, A. J., Ouellette M., Danagoulian J., Wernsing G., Liu T. T., Savig E., Suzek B. E., Rubin D. L., and Paik D. , J Digit ImagingJournal of Digital Imaging, Aug, Volume 26, Number 4, p.630-41, (2013)
Semi-automatic geographic atrophy segmentation for SD-OCT images, Chen, Q., de Sisternes L., Leng T., Zheng L., Kutzscher L., and Rubin D. L. , Biomed Opt ExpressBiomed Opt Express, Volume 4, Number 12, p.2729-50, (2013)
Snake model-based lymphoma segmentation for sequential CT images, Chen, Q., Quan F., Xu J., and Rubin D. L. , Comput Methods Programs BiomedComput Methods Programs Biomed, Aug, Volume 111, Number 2, p.366-75, (2013)
2012
ACR-AAPM-SIIM Practice Guideline for Determinants of Image Quality in Digital Mammography, Kanal, K. M., Krupinski E., Berns E. A., Geiser W. R., Karellas A., Mainiero M. B., Martin M. C., Patel S. B., Rubin D. L., Shepard J. D., et al. , J Digit Imaging, Sep 20, (2012)
Automatic annotation of radiological observations in liver CT images, Gimenez, F., Xu J., Liu Y., Liu T., Beaulieu C., Rubin D., and Napel S. , AMIA Annu Symp Proc, Volume 2012, p.257-63, (2012)
Automatic classification of mammography reports by BI-RADS breast tissue composition class, Percha, B., Nassif H., Lipson J., Burnside E., and Rubin D. , J Am Med Inform Assoc, Sep-Oct, Volume 19, Number 5, p.913-6, (2012)
Biomedical Imaging Informatics, Rubin, D. L., Greenspan H., and Brinkley J. F. , Biomedical Informatics: Computer Applications in Health Care and Biomedicine, New York, NY, (2012)
Finding the Meaning in Images: Annotation and Image Markup, Rubin, D. L. , Philosophy, Psychiatry, and Psychology, Volume 18, Number 4, (2012)
Informatics in radiology: An open-source and open-access cancer biomedical informatics grid annotation and image markup template builder, Mongkolwat, P., Channin D. S., Kleper V., and Rubin D. L. , Radiographics, Jul-Aug, Volume 32, Number 4, p.1223-32, (2012)
Informatics in Radiology: Improving Clinical Work Flow through an AIM Database: A Sample Web-based Lesion Tracking Application, Abajian, A. C., Levy M., and Rubin D. L. , Radiographics, Sep, Volume 32, Number 5, p.1543-52, (2012)
Informatics methods to enable sharing of quantitative imaging research data, Levy, M. A., Freymann J. B., Kirby J. S., Fedorov A., Fennessy F. M., Eschrich S. A., Berglund A. E., Fenstermacher D. A., Tan Y., Guo X., et al. , Magn Reson Imaging, Nov, Volume 30, Number 9, p.1249-56, (2012)
Integration of imaging signs into RadLex, Shore, M. W., Rubin D. L., and Kahn, Jr. C. E. , J Digit ImagingJournal of Digital Imaging, Feb, Volume 25, Number 1, p.50-5, (2012)
Modeling Perceptual Similarity Measures in CT Images of Focal Liver Lesions, Faruque, J., Rubin D. L., Beaulieu C. F., and Napel S. , J Digit Imaging, Dec 20, (2012)
Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data--methods and preliminary results, Gevaert, O., Xu J., Hoang C. D., Leung A. N., Xu Y., Quon A., Rubin D. L., Napel S., and Plevritis S. K. , RadiologyRadiology, Aug, Volume 264, Number 2, p.387-96, (2012)

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