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Daniela Raicu
Daniela Stan Raicu – Daniela Stan
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2020 – today
- 2024
- [j19]Priya Deshpande, Alexander Rasin, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu, Michiel Schinkel, Hari Trivedi
, Sameer K. Antani:
Biomedical heterogeneous data categorization and schema mapping toward data integration. Frontiers Big Data 6 (2024) - 2023
- [c101]Arun Sivakumar, Yiyang Wang
Curriculum gDRO: Improving Lung Malignancy Classification through Robust Curriculum Task Learning. CBMS 2023: 622-627 - [c100]Crystal Contreras
Multiclass Classification of Software Vulnerabilities with Deep Learning. ICMLC 2023: 134-140 - [c99]Katherine Aubert, Catherine Huber, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua:
Iterative K-means clustering for disease subtype discovery. Medical Imaging: Computer-Aided Diagnosis 2023 - [c98]Thomas Zeng, Elias Furst, Yiyang Wang
No nodule left behind: evaluating lung nodule malignancy classification with different stratification schemes. Medical Imaging: Computer-Aided Diagnosis 2023 - 2022
- [c97]Abigail Keller, Jacob Furst, Daniela Raicu, Peter M. Hastings, Roselyne Tchoua:
Text Summarization towards Scientific Information Extraction. e-Science 2022: 225-235 - [c96]Mirtha Lucas
Explainable Model for Localization of Spiculation in Lung Nodules. ECCV Workshops (7) 2022: 457-471 - [c95]Jennifer Schwabe, Chelsea Hua
Predicting ME/CFS After Infectious Mononucleosis Using Cytokine Network Correlations. ICMLA 2022: 555-559 - [c94]Yiyang Wang
Lung Nodule Malignancy Subtype Discovery with Semantic Learning. ICPR 2022: 4234-4240 - [c93]Mirtha Lucas
RSI-Grad-CAM: Visual Explanations from Deep Networks via Riemann-Stieltjes Integrated Gradient-Based Localization. ISVC (1) 2022: 262-274 - [c92]Suhev Shakya, Mariana Vasquez, Yiyang Wang
Human-in-the-loop deep learning retinal image classification with customized loss function. Medical Imaging: Computer-Aided Diagnosis 2022 - [c91]Claire Weissman, Lilly Roelofs, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua:
Similarity-based uncertainty scores for computer-aided diagnosis. Medical Imaging: Computer-Aided Diagnosis 2022 - [c90]Mariana Vasquez, Suhev Shakya, Ian Wang, Jacob Furst, Roselyne Tchoua, Daniela Raicu:
Interactive deep learning for explainable retinal disease classification. Medical Imaging: Image Processing 2022 - [c89]Jennifer Piane, Yiyang Wang
Autorevise: annotation refinement using motion signal patterns. SAC 2022: 81-84 - [c88]Lilly Roelofs, Claire Weissman, Daniela Raicu, Jacob Furst, Roselyne Tchoua:
Similarity-based uncertainty scores for interpretable deep learning in scientific applications. SAC 2022: 1152-1155 - [c87]Edward Xu, Thiruvarangan Ramaraj, Roselyne Tchoua, Jacob Furst, Daniela Raicu:
Contextualizing Lung Nodule Malignancy Predictions with Easy vs. Hard Image Classification. TransAI 2022: 122-127 - [i3]Mirtha Lucas, Miguel Lerma, Jacob Furst, Daniela Raicu:
Visual Explanations from Deep Networks via Riemann-Stieltjes Integrated Gradient-based Localization. CoRR abs/2205.10900 (2022) - [i2]Bowen Qiu, Daniela Raicu, Jacob Furst, Roselyne Tchoua:
CompNet: A Designated Model to Handle Combinations of Images and Designed features. CoRR abs/2209.14454 (2022) - 2021
- [c86]Amal N. Almansour, Jacob Furst, Daniela Raicu, Enid Montague
Approaches to Evaluating Eye Gaze Patterns between Physician-Patient Interaction in Primary Care Clinic. BIBM 2021: 1245-1250 - [c85]Erin Murphy, Alexander Rasin, Jacob Furst, Daniela Raicu, Roselyne Tchoua:
Ensemble Labeling towards Scientific Information Extraction (ELSIE) - Blob Extraction. e-Science 2021: 11-20 - [c84]Erin Murphy
Ensemble Labeling Towards Scientific Information Extraction (ELSIE). ICCS (1) 2021: 750-764 - [c83]Abum Okemgbo
Drusen segmentation with sparse volumetric SD-OCT sampling. Medical Imaging: Image Processing 2021 - [e3]M. Arif Wani, Ishwar K. Sethi, Weisong Shi, Guangzhi Qu, Daniela Stan Raicu, Ruoming Jin:
20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021, Pasadena, CA, USA, December 13-16, 2021. IEEE 2021, ISBN 978-1-6654-4337-1 [contents] - 2020
- [j18]Priya Deshpande, Alexander Rasin, Jun Son, Sungmin Kim, Eli T. Brown, Jacob Furst, Daniela Stan Raicu, Steven M. Montner, Samuel G. Armato:
Ontology-Based Radiology Teaching File Summarization, Coverage, and Integration. J. Digit. Imaging 33(3): 797-813 (2020) - [c82]Arun Gopal Govindaswamy, Enid Montague
CNN as a feature extractor in gaze recognition. AICCC 2020: 31-37 - [c81]Yiyang Wang
Explainable Deep Learning for Biomarker Classification of OCT Images. BIBE 2020: 204-210 - [c80]Mirtha Lucas, Miguel Lerma, Jacob Furst, Daniela Raicu:
Heatmap Template Generation for COVID-19 Biomarker Detection in Chest X-rays. BIBE 2020: 438-445 - [c79]Tianyi Tan, Enid Montague
Robust Physician Gaze Prediction Using a Deep Learning Approach. BIBE 2020: 993-998 - [c78]Mengyuan Shang, Jacob Furst, Daniela Stan Raicu:
Assessment of Medical Reports Uncertainty through Topic Modeling and Machine Learning. CBMS 2020: 189-192 - [c77]Priya Deshpande, Alexander Rasin, Roselyne Tchoua, Jacob Furst, Daniela Raicu, Sameer K. Antani:
Enhancing Recall Using Data Cleaning for Biomedical Big Data. CBMS 2020: 265-270 - [c76]Bowen Qiu, Jacob Furst, Alexander Rasin, Roselyne Tchoua, Daniela Raicu:
Learning Latent Spiculated Features for Lung Nodule Characterization. EMBC 2020: 1254-1257 - [c75]Tianyi Tan, Enid Montague
Developing Parameters for a Technology to Predict Patient Satisfaction in Naturalistic Clinical Encounters. HCI (18) 2020: 473-490 - [c74]Arun G. Govindaswamy, Enid Montague
Predicting physician gaze in clinical settings using optical flow and positioning. IVCNZ 2020: 1-6 - [c73]Yiyang Wang
Detecting age-related macular degeneration (AMD) biomarker images using MFCC and texture features. Medical Imaging: Computer-Aided Diagnosis 2020 - [c72]Elise Glaser, Alexander Morain, Jonathan Gemmell, Daniela Raicu:
Comparing automatically extracted topics from online suicidal ideation and the responses they invoke. SAC 2020: 1818-1825
2010 – 2019
- 2019
- [j17]Priya Deshpande
DiiS: A Biomedical Data Access Framework for Aiding Data Driven Research Supporting FAIR Principles. Data 4(2): 54 (2019) - [j16]Bamshad Mobasher, Lucia Dettori, Daniela Raicu, Raffaella Settimi, Nasim Sonboli, Monica Stettler:
Data Science Summer Academy for Chicago Public School Students. SIGKDD Explor. 21(1): 49-52 (2019) - [c71]Jennifer Piane, Yiyang Wang
Augmenting Frame-based with Window-based Features for C. elegans Movement Classification. BHI 2019: 1-4 - [c70]Daniel Gutstein, Enid Montague
Hand-Eye Coordination: Automating the Annotation of Physician-Patient Interactions. BIBE 2019: 657-662 - [c69]Daniel Gutstein, Enid Montague
Optical Flow, Positioning, and Eye Coordination: Automating the Annotation of Physician-Patient Interactions. BIBM 2019: 943-947 - [c68]Priya Deshpande, Alexander Rasin, Fang Cao, Sriram Yarlagadda, Eli T. Brown, Jacob Furst, Daniela Stan Raicu:
Multimodal Ranked Search over Integrated Repository of Radiology Data Sources. KDIR 2019: 372-383 - [c67]Samah J. Fodeh, Taihua Li, Kevin Menczynski, Tedd Burgette, Andrew Harris, Georgeta Ilita, Satyan Rao, Jonathan Gemmell, Daniela Raicu:
Using Machine Learning Algorithms to Detect Suicide Risk Factors on Twitter. ICDM Workshops 2019: 941-948 - [c66]Yan Yu
Identifying Diagnostically Complex Cases Through Ensemble Learning. ICIAR (2) 2019: 316-324 - [c65]Samuel Berglin, Eura Shin, Jacob Furst, Daniela Raicu:
Efficient learning in computer-aided diagnosis through label propagation. Medical Imaging: Computer-Aided Diagnosis 2019: 109501I - [c64]Chufan Gao, Stephen Clark, Jacob Furst, Daniela Raicu:
Augmenting LIDC dataset using 3D generative adversarial networks to improve lung nodule detection. Medical Imaging: Computer-Aided Diagnosis 2019: 109501K - [c63]Eura Shin, Samuel Berglin, Jacob Furst, Daniela Raicu:
Expanding annotated data with informed labels for weak supervision. MLDM (2) 2019: 571-584 - 2018
- [j15]Reilly Grant, David Kucher, Ana M. Leon, Jonathan Gemmell, Daniela Stan Raicu, Samah J. Fodeh:
Automatic extraction of informal topics from online suicidal ideation. BMC Bioinform. 19-S(8): 57-66 (2018) - [j14]Priya Deshpande, Alexander Rasin, Eli T. Brown, Jacob Furst, Steven M. Montner, Samuel G. Armato III, Daniela Stan Raicu:
Augmenting Medical Decision Making With Text-Based Search of Teaching File Repositories and Medical Ontologies: Text-Based Search of Radiology Teaching Files. Int. J. Knowl. Discov. Bioinform. 8(2): 18-43 (2018) - [c62]Dante Chakravorti, Kathleen Law, Jonathan Gemmell, Daniela Raicu:
Detecting and Characterizing Trends in Online Mental Health Discussions. ICDM Workshops 2018: 697-706 - [c61]Jake N. Sauter, Victoria M. LaBarre, Jacob D. Furst, Daniela Stan Raicu:
An evaluation of consensus techniques for diagnostic interpretation. Medical Imaging: Computer-Aided Diagnosis 2018: 1057538 - [c60]Natalia M. Jenuwine, Sunny N. Mahesh, Jacob D. Furst, Daniela Stan Raicu:
Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selection. Medical Imaging: Computer-Aided Diagnosis 2018: 1057539 - [i1]Matthew Yung, Eli T. Brown, Alexander Rasin, Jacob D. Furst, Daniela Stan Raicu:
Synthetic Sampling for Multi-Class Malignancy Prediction. CoRR abs/1807.02608 (2018) - 2017
- [c59]Sarah Bishara, Jennifer Baltes, Taha Hamid, Taihua Li, Denise C. Nacu, Caitlin Kennedy Martin, Jonathan Gemmell, Chris MacArthur, Daniela Raicu, Nichole Pinkard:
Revealing Interaction Patterns Among Youth in an Online Social Learning Network Using Markov Chain Principles. CSCL 2017 - [c58]Reilly Grant, David Kucher, Ana M. Leon, Jonathan Gemmell, Daniela Raicu:
Discovery of Informal Topics from Post Traumatic Stress Disorder Forums. ICDM Workshops 2017: 452-461 - [c57]Priya Deshpande, Alexander Rasin, Eli T. Brown, Jacob Furst, Daniela Raicu, Steven M. Montner, Samuel G. Armato III:
An Integrated Database and Smart Search Tool for Medical Knowledge Extraction from Radiology Teaching Files. MIH@KDD 2017: 10-18 - [c56]Rachael N. Affenit, Erik R. Barns, Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu:
Building confidence and credibility into CAD with belief decision trees. Medical Imaging: Computer-Aided Diagnosis 2017: 101343Z - [e2]Samah J. Fodeh, Daniela Stan Raicu:
Proceedings of the 1st ACM Workshop on Medical Informatics and Healthcare, MIH 2017, Halifax, Nova Scotia, Canada, August 14, 2017. Proceedings of Machine Learning Research 69, PMLR 2017 [contents] - 2016
- [j13]Huang Li
A Run-Length Encoding Approach for Path Analysis of C. elegans Search Behavior. Comput. Math. Methods Medicine 2016: 3516089:1-3516089:9 (2016) - [c55]Mohamed El-Dirany, Forrest Wang, Jacob Furst, John Rogers, Daniela Raicu:
Compression-based distance methods as an alternative to statistical methods for constructing phylogenetic trees. BIBM 2016: 1107-1112 - [c54]Yiyang Wang
C. elegans search behavior analysis using Multivariate Dynamic Time Warping. BIBM 2016: 1569-1576 - [c53]Miguel Carrazza, Brendan Kennedy
Investigating the effects of majority voting on CAD systems: a LIDC case study. Medical Imaging: Computer-Aided Diagnosis 2016: 978533 - [c52]Taha Hamid, Denise C. Nacu, Taihua Li, Jonathan Gemmell, Daniela Stan Raicu, Caitlin Kennedy Martin, Michael Schutzenhofer, Nichole Pinkard:
Recommender System to Support Brokering of Youth Learning Opportunities. WI Workshops 2016: 64-65 - 2015
- [j12]Jose R. Zamacona, Ronald Niehaus, Alexander Rasin, Jacob D. Furst, Daniela Stan Raicu:
Assessing diagnostic complexity: An image feature-based strategy to reduce annotation costs. Comput. Biol. Medicine 62: 294-305 (2015) - [j11]Ronald Niehaus, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis. J. Digit. Imaging 28(6): 704-717 (2015) - [c51]Brendan Kennedy
Applying Association Rule Mining to Semantic Data in the Lung Image Database Consortium. ICDM Workshops 2015: 463-471 - [c50]Amelia Riely, Kyle Sablan, Thomas Xiaotao, Jacob Furst, Daniela Raicu:
Reducing annotation cost and uncertainty in computer-aided diagnosis through selective iterative classification. Medical Imaging: Computer-Aided Diagnosis 2015: 94141K - [c49]Elza Margolin, Jacob Furst, Daniela Raicu:
An outlier filtering approach for machine sourced weak segmentations. Medical Imaging: Computer-Aided Diagnosis 2015: 94142Q - [c48]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Identifying the optimal segmentors for mass classification in mammograms. Medical Imaging: Image Processing 2015: 941342 - 2014
- [c47]Mike Seidel, Alexander Rasin, Jacob Furst, Daniela Stan Raicu:
Towards Achieving Diagnostic Consensus in Medical Image Interpretation. ICDM Workshops 2014: 771-780 - [c46]Mayra Alejandra Molina Puentes, Jacob Furst, Daniela Stan Raicu:
Machine-Sourced Segmentations vs. Expert-Sourced Segmentations for the Classification of Lung Nodules with Outlier Removal. ICMLA 2014: 510-515 - 2013
- [c45]Jennifer Piane, Daniela Raicu, Jacob Furst:
Training industrial robots with gesture recognition techniques. Intelligent Robots and Computer Vision: Algorithms and Techniques 2013: 86620I - [c44]Jose R. Zamacona, Alexander Rasin, Jacob D. Furst, Daniela Stan Raicu:
Reducing Classification Cost through Strategic Annotation Assignment. ICDM Workshops 2013: 287-294 - [c43]Ethan Smith, Patrick Stein, Jacob Furst, Daniela Stan Raicu:
Weak Segmentations and Ensemble Learning to Predict Semantic Ratings of Lung Nodules. ICMLA (2) 2013: 519-524 - [c42]Sydney Williams
Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers. MLDM 2013: 644-657 - 2012
- [j10]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Building an ensemble system for diagnosing masses in mammograms. Int. J. Comput. Assist. Radiol. Surg. 7(2): 323-329 (2012) - [j9]Dmitry Zinovev, Yujie Duo, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
Consensus Versus Disagreement in Imaging Research: a Case Study Using the LIDC Database. J. Digit. Imaging 25(3): 423-436 (2012) - [c41]Anne-Marie Giuca, Kerry A. Seitz
Expanding diagnostically labeled datasets using content-based image retrieval. ICIP 2012: 2397-2400 - [c40]Kerry A. Seitz
Learning lung nodule similarity using a genetic algorithm. Medical Imaging: Computer-Aided Diagnosis 2012: 831537 - 2011
- [j8]Pia Opulencia, David S. Channin
Mapping LIDC, RadLex™, and Lung Nodule Image Features. J. Digit. Imaging 24(2): 256-270 (2011) - [c39]Dmitry Zinovev, Jonathan Feigenbaum, Jacob Furst, Daniela Raicu:
Probabilistic lung nodule classification with belief decision trees. EMBC 2011: 4493-4498 - [c38]Olga Zinoveva, Dmitry Zinovev, Stephen A. Siena, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
A Texture-Based Probabilistic Approach for Lung Nodule Segmentation. ICIAR (2) 2011: 21-30 - [c37]Dmitry Zinovev, Jacob Furst, Daniela Stan Raicu:
Building an Ensemble of Probabilistic Classifiers for Lung Nodule Interpretation. ICMLA (2) 2011: 155-161 - [c36]Jacob V. Gardner, Daniela Raicu, Jacob Furst:
A context-aware approach to content-based image retrieval of lung nodules. Medical Imaging: Computer-Aided Diagnosis 2011: 79632I - [c35]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Building multiple weak segmentors for strong mass segmentation in mammogram. Medical Imaging: Image Processing 2011: 796233 - [c34]Hans-Peter Bischof, Jacob D. Furst, Daniela Stan Raicu, Susan Darling Urban:
Top issues in providing successful undergraduate research experiences. SIGCSE 2011: 239-240 - 2010
- [c33]Zahra Ferdowsi, Raffaella Settimi, Daniela Stan Raicu:
An Application of Clustering Techniques to Urban Studies. DMIN 2010: 158-164 - [c32]William H. Horsthemke, Daniela Stan Raicu, Jacob D. Furst:
Predicting LIDC diagnostic characteristics by combining spatial and diagnostic opinions. Medical Imaging: Computer-Aided Diagnosis 2010: 76242Y - [c31]Stephen A. Siena, Olga Zinoveva, Daniela Raicu, Jacob Furst, Samuel G. Armato:
A shape-dependent variability metric for evaluating panel segmentations with a case study on LIDC. Medical Imaging: Computer-Aided Diagnosis 2010: 762416 - [c30]Grace M. Dasovich, Robert Kim, Daniela Stan Raicu, Jacob D. Furst:
A model for the relationship between semantic and content based similarity using LIDC. Medical Imaging: Computer-Aided Diagnosis 2010: 762431 - [c29]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Image enhancement and edge-based mass segmentation in mammogram. Medical Imaging: Image Processing 2010: 76234P - [c28]Robert Kim, Grace Dasovich, Runa Bhaumik, Richard Brock, Jacob D. Furst, Daniela Stan Raicu:
An investigation into the relationship between semantic and content based similarity using LIDC. Multimedia Information Retrieval 2010: 185-192
2000 – 2009
- 2009
- [j7]Dmitry Zinovev, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
Predicting Radiological Panel Opinions Using a Panel of Machine Learning Classifiers. Algorithms 2(4): 1473-1502 (2009) - [j6]Dmitry Zinovev, Ekarin Varutbangkul, Daniela Stan Raicu, Jacob D. Furst, Samuel G. Armato III:
Semi-supervised learning approaches for predicting semantic characteristics of lung nodules. Intell. Decis. Technol. 3(4): 207-217 (2009) - [j5]William H. Horsthemke, Daniela Stan Raicu, Jacob D. Furst:
Evaluation Challenges for Bridging Semantic Gap: Shape Disagreements on Pulmonary Nodules in the Lung Image Database Consortium. Int. J. Heal. Inf. Syst. Informatics 4(1): 17-33 (2009) - [j4]Tobias Heimann, Bram van Ginneken
Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets. IEEE Trans. Medical Imaging 28(8): 1251-1265 (2009) - [c27]Jonathan Mortensen, Jia Jie Wu, Jacob Furst, John Rogers, Daniela Raicu:
Effect of Image Linearization on Normalized Compression Distance. FGIT-SIP 2009: 106-116 - [c26]Joseph S. Wantroba, Daniela Stan Raicu, Jacob D. Furst:
A statistical analysis of the effects of CT acquisition parameters on low-level features extracted from CT images of the lung. ICIP 2009: 4197-4200 - [c25]William H. Horsthemke, Daniela Stan Raicu, Jacob D. Furst:
Characterizing pulmonary nodule shape using a boundary-region approach. Medical Imaging: Computer-Aided Diagnosis 2009: 72602Y - [c24]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Using BI-RADS Descriptors and Ensemble Learning for Classifying Masses in Mammograms. MCBR-CDS 2009: 69-76 - [c23]Daniela Stan Raicu, Jacob David Furst:
Enhancing undergraduate education: a REU model for interdisciplinary research. SIGCSE 2009: 468-472 - 2008
- [c22]Carl Philips, Daniel Li, Daniela Stan Raicu, Jacob Furst:
Directional Invariance of Co-occurrence Matrices within the Liver. BIOTECHNO 2008: 29-34 - [c21]Ekarin Varutbangkul, Vesna Mitrovic, Daniela Stan Raicu, Jacob Furst:
Combining Boundaries and Ratings from Multiple Observers for Predicting Lung Nodule Characteristics. BIOTECHNO 2008: 82-87 - [c20]Aaron M. Mintz, Daniela Stan Raicu, Jacob D. Furst:
Liver segmentation combining Gabor filtering and traditional vector field snake. Medical Imaging: Image Processing 2008: 69141H - [c19]Ruchaneewan Susomboon, Daniela Raicu, Jacob Furst, Timothy Ben Johnson:
A co-occurrence texture semi-invariance to direction, distance, and patient size. Medical Imaging: Image Processing 2008: 69141Y - [e1]Rita Casadio, Ovidiu Daescu, Cosmin Dini, Daniela Stan Raicu:
International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies, BIOTECHNO 2008, June 29 - July 5, 2008, Bucharest, Romania. IEEE Computer Society 2008, ISBN 978-0-7695-3191-5 [contents] - 2007
- [j3]Michael V. Doran, Daniela Stan Raicu, Jacob D. Furst, Raffaella Settimi, Matthew Schipma, Darrell P. Chandler:
Oligonucleotide microarray identification of Bacillus anthracis strains using support vector machines. Bioinform. 23(4): 487-492 (2007) - [c18]William H. Horsthemke, Ekarin Varutbangkul, Daniela Stan Raicu, Jacob Furst:
Predictive Data Mining for Lung Nodule Interpretation. ICDM Workshops 2007: 157-162 - [c17]Daniela Stan Raicu, Ekarin Varutbangkul, Janie G. Cisneros, Jacob Furst, David S. Channin, Samuel G. Armato:
Semantics and image content integration for pulmonary nodule interpretation in thoracic computed tomography. Medical Imaging: Image Processing 2007: 65120S - [c16]William H. Horsthemke, Daniela Stan Raicu:
Organ analysis and classification using principal component and linear discriminant analysis. Medical Imaging: Image Processing 2007: 65124A - [c15]Mailan Pham, Ruchaneewan Susomboon, Tim Disney, Daniela Raicu, Jacob Furst:
A comparison of texture models for automatic liver segmentation. Medical Imaging: Image Processing 2007: 65124E - [c14]Sharon I. Greenblum, Max Krucoff, Jacob Furst, Daniela Stan Raicu:
Automated image analysis of noisy microarrays. VISAPP (1) 2007: 371-375 - 2006
- [j2]Daniela Stan Raicu, Ishwar K. Sethi
Synobins: An Intermediate Level towards Annotation and Semantic Retrieval. EURASIP J. Adv. Signal Process. 2006 (2006) - [c13]Nathan J. Backman, Brian W. Whitney, Jacob D. Furst, Daniela Stan Raicu:
A prioritized and adaptive approach to volumetric seeded region growing using texture descriptors. Computational Imaging 2006: 60651A - [c12]Jacob D. Furst, Ruchaneewan Susomboon, Daniela Stan Raicu:
Single Organ Segmentation Filters for Multiple Organ Segmentation. EMBC 2006: 3033-3036 - [c11]Ruchaneewan Susomboon, Daniela Stan Raicu, Jacob Furst, David S. Channin:
Automatic Single-Organ Segmentation in Computed Tomography Images. ICDM 2006: 1081-1086 - [c10]Stefanie Handrick, Bahare Naimipour, Daniela Raicu, Jacob Furst:
Evaluation of binning strategies for tissue classification in computed tomography images. Medical Imaging: Image Processing 2006: 61444L - [c9]Brian W. Whitney, Nathan J. Backman, Jacob D. Furst, Daniela Stan Raicu:
Single click volumetric segmentation of abdominal organs in computed tomography images. Medical Imaging: Image Processing 2006: 61444G - [c8]Roman Lerman, Daniela Stan Raicu, Jacob D. Furst:
Contrast enhancement of soft tissues in computed tomography images. Medical Imaging: Image Processing 2006: 61446M - 2005
- [c7]Winnie Tsang, Andrew Corboy, Ken Lee, Daniela Stan Raicu, Jacob Furst:
Texture-Based Image Retrieval for Computerized Tomography Databases. CBMS 2005: 593-598 - [c6]Mikhail Kalinin, Daniela Stan Raicu, Jacob D. Furst, David S. Channin:
A classification approach for anatomical regions segmentation. ICIP (2) 2005: 1262-1265 - 2003
- [j1]Daniela Stan, Ishwar K. Sethi
eID: a system for exploration of image databases. Inf. Process. Manag. 39(3): 335-361 (2003) - [c5]Daniela Stan Raicu:
A Data Mining Framework for Target Marketing. CATA 2003: 476-479 - 2002
- [c4]Daniela Stan, Ishwar K. Sethi:
Color patterns for pictorial content description. SAC 2002: 693-698 - 2001
- [c3]Ishwar K. Sethi
Mining association rules between low-level image features and high-level concepts. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2001: 279-290 - [c2]Daniela Stan, Ishwar K. Sethi:
Image Retrieval Using a Hierarchy of Clusters. ICAPR 2001: 377-386 - [c1]Daniela Stan, Ishwar K. Sethi
Mapping low-level image features to semantic concepts. Storage and Retrieval for Media Databases 2001: 172-179
Coauthor Index
[j19] [c101] [c100] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c91] [c90] [c89] [c88] [c87] [i3] [i2] [c86] [c85] [c84] [c83] [j18] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [c75] [c74] [c73] [j17] [c71] [c70] [c69] [c68] [c66] [c65] [c64] [c63] [j14] [c61] [c60] [i1] [c57] [c56] [j13] [c55] [c54] [c53] [j12] [j11] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [j10] [j9] [c41] [c40] [j8] [c39] [c38] [c37] [c36] [c35] [c34] [c32] [c31] [c30] [c29] [c28] [j7] [j6] [j5] [j4] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [j3] [c18] [c17] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6]
Alexander Rasin
aka: Alex Rasin
aka: Alex Rasin
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last updated on 2024-10-07 21:14 CEST by the dblp team
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