Daniela Stan Raicu

发表

Applying Association Rule Mining to Semantic Data in the Lung Image Database Consortium

Jacob D. Furst, Brendan Kennedy, Miguel Carrazza, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Top issues in providing successful undergraduate research experiences

Jacob D. Furst, Daniela Stan Raicu, Hans-Peter Bischof, 2011, SIGCSE.

Synobins: An Intermediate Level towards Annotation and Semantic Retrieval

Ishwar K. Sethi, Daniela Stan Raicu, 2006, EURASIP J. Adv. Signal Process..

An evaluation of consensus techniques for diagnostic interpretation

Jacob D. Furst, Daniela Stan Raicu, Jake N. Sauter, 2018, Medical Imaging.

Predictive Data Mining for Lung Nodule Interpretation

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Evaluation Challenges for Bridging Semantic Gap: Shape Disagreements on Pulmonary Nodules in the Lung Image Database Consortium

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2009, Int. J. Heal. Inf. Syst. Informatics.

Building an Ensemble of Probabilistic Classifiers for Lung Nodule Interpretation

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Combining Boundaries and Ratings from Multiple Observers for Predicting Lung Nodule Characteristics

Jacob D. Furst, Daniela Stan Raicu, Ekarin Varutbangkul, 2008, 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies.

Assessing diagnostic complexity: An image feature-based strategy to reduce annotation costs

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2015, Comput. Biol. Medicine.

Local versus global texture analysis for lung nodule image retrieval

Jacob D. Furst, Daniela Stan Raicu, Ryan Datteri, 2008, SPIE Medical Imaging.

An Application of Clustering Techniques to Urban Studies

Daniela Stan Raicu, Raffaella Settimi, Zahra Ferdowsi, 2010, DMIN.

An investigation into the relationship between semantic and content based similarity using LIDC

Jacob D. Furst, Daniela Stan Raicu, Richard Brock, 2010, MIR '10.

Characterizing pulmonary nodule shape using a boundary-region approach

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2009, Medical Imaging.

RUN-LENGTH ENCODING FOR VOLUMETRIC TEXTURE

Jacob D. Furst, Daniela Stan Raicu, Dong-Hui Xu, 2004 .

Mapping low-level image features to semantic concepts

Ishwar K. Sethi, Daniela Stan Raicu, 2001, IS&T/SPIE Electronic Imaging.

Analysis of a Proposed Universal Fingerprint Microarray

Jacob D. Furst, Daniela Stan Raicu, Raffaella Settimi, 2006 .

Synthetic Sampling for Multi-Class Malignancy Prediction pdf

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2018, ArXiv.

Building multiple weak segmentors for strong mass segmentation in mammogram

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2011, Medical Imaging.

Content-based image retrieval for pulmonary computed tomography nodule images

Jacob D. Furst, Daniela Stan Raicu, Tim Disney, 2007, SPIE Medical Imaging.

Mapping LIDC, RadLex™, and Lung Nodule Image Features

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2011, Journal of Digital Imaging.

Recommender System to Support Brokering of Youth Learning Opportunities

Daniela Stan Raicu, Taihua Li, Jonathan Gemmell, 2016, 2016 IEEE/WIC/ACM International Conference on Web Intelligence Workshops (WIW).

Image Retrieval Using a Hierarchy of Clusters

Ishwar K. Sethi, Daniela Stan Raicu, 2001, ICAPR.

Oligonucleotide Microarray Identification of Bacillus Anthracis Strains Using Support Vector Machines

Jacob D. Furst, Daniela Stan Raicu, Michael V. Doran, 2007 .

Predictive Data Mining for Lung Nodule Interpretation

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2007 .

International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies, BIOTECHNO 2008, June 29 - July 5, 2008, Bucharest, Romania

Ovidiu Daescu, Daniela Stan Raicu, Rita Casadio, 2008, BIOTECHNO.

Preface to data mining in biomedical informatics and healthcare

Paulo J. G. Lisboa, Jacob D. Furst, Hamidreza Chitsaz, 2013, ICDM 2013.

Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers

Jacob D. Furst, Daniela Stan Raicu, Michael Harris, 2013, MLDM.

Identifying the optimal segmentors for mass classification in mammograms

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2015, Medical Imaging.

Weak Segmentations and Ensemble Learning to Predict Semantic Ratings of Lung Nodules

Jacob D. Furst, Daniela Stan Raicu, Patrick Stein, 2013, 2013 12th International Conference on Machine Learning and Applications.

Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis

Jacob D. Furst, Daniela Stan Raicu, Samuel G. Armato, 2015, Journal of Digital Imaging.

Liver segmentation combining Gabor filtering and traditional vector field snake

Jacob D. Furst, Daniela Stan Raicu, Aaron M. Mintz, 2008, SPIE Medical Imaging.

Training industrial robots with gesture recognition techniques

Jacob D. Furst, Daniela Stan Raicu, Jennifer Piane, 2013, Electronic Imaging.

Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selection

Jacob D. Furst, Daniela Stan Raicu, Natalia M. Jenuwine, 2018, Medical Imaging.

A Texture Dictionary for Human Organs Tissues’ Classification

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2004 .

Towards Achieving Diagnostic Consensus in Medical Image Interpretation

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2014, 2014 IEEE International Conference on Data Mining Workshop.

Contrast enhancement of soft tissues in computed tomography images

Jacob D. Furst, Daniela Stan Raicu, Roman Lerman, 2006, SPIE Medical Imaging.

Consensus Versus Disagreement in Imaging Research: a Case Study Using the LIDC Database

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2012, Journal of Digital Imaging.

Automatic Single-Organ Segmentation in Computed Tomography Images

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2006, Sixth International Conference on Data Mining (ICDM'06).

Directional Invariance of Co-occurrence Matrices within the Liver

Jacob D. Furst, Daniela Stan Raicu, Daniel Li, 2008, 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies.

Semantics and image content integration for pulmonary nodule interpretation in thoracic computed tomography

Jacob D. Furst, Samuel G. Armato, Daniela Stan Raicu, 2007, SPIE Medical Imaging.

Predicting LIDC diagnostic characteristics by combining spatial and diagnostic opinions

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2010, Medical Imaging.

Predicting Radiological Panel Opinions Using a Panel of Machine Learning Classifiers

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2009, Algorithms.

Enhancing undergraduate education: a REU model for interdisciplinary research

Jacob D. Furst, Daniela Stan Raicu, J. Furst, 2009, SIGCSE '09.

Semi-supervised learning approaches for predicting semantic characteristics of lung nodules

Jacob D. Furst, Daniela Stan Raicu, Ekarin Varutbangkul, 2009, Intell. Decis. Technol..

Image enhancement and edge-based mass segmentation in mammogram

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2010, Medical Imaging.

Mining Knowledge in Computer Tomography Image Databases

Daniela Stan Raicu, D. Raicu, 2007 .

Building confidence and credibility into CAD with belief decision trees

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2017, Medical Imaging.

Multimodal Ranked Search over Integrated Repository of Radiology Data Sources

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2019, KDIR.

Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets

Martin Styner, Jacob D. Furst, Thomas Lange, 2009, IEEE Transactions on Medical Imaging.

A model for the relationship between semantic and content based similarity using LIDC

Jacob D. Furst, Daniela Stan Raicu, Robert Kim, 2010, Medical Imaging.

Using BI-RADS Descriptors and Ensemble Learning for Classifying Masses in Mammograms

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2009, MCBR-CDS.

A classification approach for anatomical regions segmentation

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2005, IEEE International Conference on Image Processing 2005.

Content-based versus semantic-based retrieval: an LIDC case study

Jacob D. Furst, Daniela Stan Raicu, Sarah A. Jabon, 2009, Medical Imaging.

Automatic extraction of informal topics from online suicidal ideation

Daniela Stan Raicu, Jonathan Gemmell, Samah J. Fodeh, 2018, BMC Bioinformatics.

Color patterns for pictorial content description

Ishwar K. Sethi, Daniela Stan Raicu, 2002, SAC '02.

Organ analysis and classification using principal component and linear discriminant analysis

Daniela Stan Raicu, William H. Horsthemke, 2007, SPIE Medical Imaging.

Texture-based image retrieval for computerized tomography databases

Jacob D. Furst, Daniela Stan Raicu, Ken Lee, 2005, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05).

Automated image analysis of noisy microarrays

Jacob D. Furst, Daniela Stan Raicu, Sharon I. Greenblum, 2007, VISAPP.

eID: a system for exploration of image databases

Ishwar K. Sethi, Daniela Stan Raicu, I. Sethi, 2003, Inf. Process. Manag..

A Lookup and Reference Tool for Pulmonary Computed Tomography Nodules

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2007 .

Texture Classification of Normal Tissues in Computed Tomography

Jacob D. Furst, Jae Min Lee, Daniela Stan Raicu, 2005 .

Privacy and Technologies of Identity

Katherine J. Strandburg, Daniela Stan Raicu, 2006 .

Building an ensemble system for diagnosing masses in mammograms

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2012, International Journal of Computer Assisted Radiology and Surgery.

Classification of Tissues in Computed Tomography using Decision Trees

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2004 .

Augmenting Medical Decision Making With Text-Based Search of Teaching File Repositories and Medical Ontologies: Text-Based Search of Radiology Teaching Files

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2018, Int. J. Knowl. Discov. Bioinform..

Assessment of Medical Reports Uncertainty through Topic Modeling and Machine Learning

Jacob D. Furst, Daniela Stan Raicu, Mengyuan Shang, 2020, 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS).

A statistical analysis of the effects of CT acquisition parameters on low-level features extracted from CT images of the lung

Jacob D. Furst, Daniela Stan Raicu, Joseph S. Wantroba, 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

Reducing Classification Cost through Strategic Annotation Assignment

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

A Texture-Based Probabilistic Approach for Lung Nodule Segmentation

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2011, ICIAR.

A prioritized and adaptive approach to volumetric seeded region growing using texture descriptors

Jacob D. Furst, Daniela Stan Raicu, Nathan J. Backman, 2006, Electronic Imaging.

A Data Mining Framework for Target Marketing

Daniela Stan Raicu, 2003, Computers and Their Applications.

Mining association rules between low-level image features and high-level concepts

Ishwar K. Sethi, Daniela Stan Raicu, Ioana L. Coman, 2001, SPIE Defense + Commercial Sensing.

Single click volumetric segmentation of abdominal organs in computed tomography images

Jacob D. Furst, Daniela Stan Raicu, Nathan J. Backman, 2006, SPIE Medical Imaging.

Machine-Sourced Segmentations vs. Expert-Sourced Segmentations for the Classification of Lung Nodules with Outlier Removal

Jacob D. Furst, Daniela Stan Raicu, Mayra Alejandra Molina Puentes, 2014, 2014 13th International Conference on Machine Learning and Applications.

Modelling semantics from image data: opportunities from LIDC

Jacob D. Furst, Samuel G. Armato, Daniela Stan Raicu, 2010 .

Texture versus shape analysis for lung nodule similarity in computed tomography studies

Jacob D. Furst, Daniela Stan Raicu, Ekarin Varutbangkul, 2008, SPIE Medical Imaging.

CO-OCCURRENCE MATRICES FOR VOLUMETRIC DATA

Jacob D. Furst, Daniela Stan Raicu, Dong-Hui Xu, 2004 .

DiiS: A Biomedical Data Access Framework for Aiding Data Driven Research Supporting FAIR Principles

Jacob D. Furst, Sameer Antani, Alexander Rasin, 2019, Data.

Expanding diagnostically labeled datasets using content-based image retrieval

Jacob D. Furst, Daniela Stan Raicu, Kerry A. Seitz, 2012, 2012 19th IEEE International Conference on Image Processing.

Privacy and Technologies of Identity: A Cross-Disciplinary Conversation

Katherine J. Strandburg, Daniela Stan Raicu, 2005 .

Investigation on Feature Selection to Improve Classification of Abdominal Organs in CT Images

Yu Zhang, Noriko Tomuro, Daniela Stan Raicu, 2006 .

A Contour-based Mass Segmentation in Mammograms

Yu Zhang, Noriko Tomuro, Daniela Stan Raicu, 2009 .