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Daniela Stan Raicu – Daniela Stan
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2020 – today
- 2024
[j21]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)- [j20]Nuvia Hernandez, Kate Karam, Nicole Baugh, Shilpa Musale, Aditya Patrick Moses, Daniela Raicu, Jacob D. Furst, Kelly McCabe, Roselyne Tchoua:
Leveraging Community Health Workers for Predicting Emergency Department Readmissions. Int. J. Semantic Comput. 18(3): 383-403 (2024) - 2023
- [c102]Arun Sivakumar, Yiyang Wang, Roselyne Tchoua, Thiruvarangan Ramaraj, Jacob Furst, Daniela Stan Raicu:
Curriculum gDRO: Improving Lung Malignancy Classification through Robust Curriculum Task Learning. CBMS 2023: 622-627 - [c101]Crystal Contreras, Hristina Dokic, Zhen Huang, Daniela Stan Raicu, Jacob Furst, Roselyne Tchoua:
Multiclass Classification of Software Vulnerabilities with Deep Learning. ICMLC 2023: 134-140 - [c100]Katherine Aubert, Catherine Huber, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua:
Iterative K-means clustering for disease subtype discovery. Computer-Aided Diagnosis 2023 - [c99]Thomas Zeng, Elias Furst, Yiyang Wang, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu:
No nodule left behind: evaluating lung nodule malignancy classification with different stratification schemes. Computer-Aided Diagnosis 2023 - [c98]Maria Alexandra Theodorescu, Jacob D. Furst, Daniela Stan Raicu, Roselyne Tchoua:
Leveraging Interpretable Features and Clustering Agreements for Assistive Materials Discovery. TransAI 2023: 71-78 - 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, Miguel Lerma, Jacob Furst, Daniela Raicu:
Explainable Model for Localization of Spiculation in Lung Nodules. ECCV Workshops (7) 2022: 457-471 - [c95]Jennifer Schwabe, Chelsea Hua, Emma M. Allen, Leonard A. Jason, Jacob Furst, Daniela Raicu:
Predicting ME/CFS After Infectious Mononucleosis Using Cytokine Network Correlations. ICMLA 2022: 555-559 - [c94]Yiyang Wang, Bowen Qiu, Thiruvarangan Ramaraj, Ilyas Ustun, Jacob Furst, Daniela Raicu:
Lung Nodule Malignancy Subtype Discovery with Semantic Learning. ICPR 2022: 4234-4240 - [c93]Mirtha Lucas, Miguel Lerma, Jacob Furst, Daniela Raicu:
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, Roselyne Tchoua, Jacob Furst, Daniela Raicu:
Human-in-the-loop deep learning retinal image classification with customized loss function. Computer-Aided Diagnosis 2022 - [c91]Claire Weissman, Lilly Roelofs, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua:
Similarity-based uncertainty scores for computer-aided diagnosis. 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. Image Processing 2022 - [c89]Jennifer Piane, Yiyang Wang, Xufan Ma, Jacob Furst, Daniela Stan Raicu:
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, Alexander Rasin, Jacob Furst, Daniela Raicu, Roselyne Tchoua:
Ensemble Labeling Towards Scientific Information Extraction (ELSIE). ICCS (1) 2021: 750-764 - [c83]Abum Okemgbo, David Rein, Yiyang Wang, Amani A. Fawzi, Jacob Furst, Daniela Raicu:
Drusen segmentation with sparse volumetric SD-OCT sampling. 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
- [j19]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, Daniela Stan Raicu, Jacob Furst:
CNN as a feature extractor in gaze recognition. AICCC 2020: 31-37 - [c81]Yiyang Wang, Mirtha Lucas, Jacob Furst, Amani A. Fawzi, Daniela Raicu:
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, Jacob Furst, Daniela Raicu:
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, Jacob Furst, Daniela Raicu:
Developing Parameters for a Technology to Predict Patient Satisfaction in Naturalistic Clinical Encounters. HCI (18) 2020: 473-490 - [c74]Arun G. Govindaswamy, Enid Montague, Daniela Raicu, Jacob Furst:
Predicting physician gaze in clinical settings using optical flow and positioning. IVCNZ 2020: 1-6 - [c73]Yiyang Wang, Xufan Ma, Rob Weddell, Abum Okemgbo, David Rein, Amani A. Fawzi, Jacob Furst, Daniela Raicu:
Detecting age-related macular degeneration (AMD) biomarker images using MFCC and texture features. 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
- [j18]Priya Deshpande, Alexander Rasin, Jacob Furst, Daniela Raicu, Sameer K. Antani:
DiiS: A Biomedical Data Access Framework for Aiding Data Driven Research Supporting FAIR Principles. Data 4(2): 54 (2019) - [j17]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, Timothy Cheung, Hongkyun Kim, Jacob Furst, Daniela Raicu:
Augmenting Frame-based with Window-based Features for C. elegans Movement Classification. BHI 2019: 1-4 - [c70]Daniel Gutstein, Enid Montague, Jacob Furst, Daniela Raicu:
Hand-Eye Coordination: Automating the Annotation of Physician-Patient Interactions. BIBE 2019: 657-662 - [c69]Daniel Gutstein, Enid Montague, Jacob Furst, Daniela Raicu:
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, Yiyang Wang, Jacob Furst, Daniela Raicu:
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. 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. 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
- [j16]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) - [j15]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. 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. 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. 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
- [j14]Huang Li, Hongkyun Kim, Jacob Furst, Daniela Raicu:
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, Carleton Smith, Mingfei Shao, Li Huang, Jacob Furst, Daniela Raicu, Hongkyun Kim:
C. elegans search behavior analysis using Multivariate Dynamic Time Warping. BIBM 2016: 1569-1576 - [c53]Miguel Carrazza, Brendan Kennedy, Alexander Rasin, Jacob Furst, Daniela Raicu:
Investigating the effects of majority voting on CAD systems: a LIDC case study. 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
- [j13]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) - [j12]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, Miguel Carrazza, Alex Rasin, Jacob Furst, Daniela Stan Raicu:
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. Computer-Aided Diagnosis 2015: 94141K - [c49]Elza Margolin, Jacob Furst, Daniela Raicu:
An outlier filtering approach for machine sourced weak segmentations. Computer-Aided Diagnosis 2015: 94142Q - [c48]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Identifying the optimal segmentors for mass classification in mammograms. 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, Michael Harris, Jacob Furst, Daniela Stan Raicu:
Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers. MLDM 2013: 644-657 - 2012
- [j11]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) - [j10]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, Jacob Furst, Daniela Stan Raicu:
Expanding diagnostically labeled datasets using content-based image retrieval. ICIP 2012: 2397-2400 - [c40]Kerry A. Seitz, Anne-Marie Giuca, Jacob Furst, Daniela Raicu:
Learning lung nodule similarity using a genetic algorithm. Computer-Aided Diagnosis 2012: 831537 - 2011
- [j9]Pia Opulencia, David S. Channin, Daniela Stan Raicu, Jacob D. Furst:
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. 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. 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. 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. 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. Computer-Aided Diagnosis 2010: 762431 - [c29]Yu Zhang, Noriko Tomuro, Jacob Furst, Daniela Stan Raicu:
Image enhancement and edge-based mass segmentation in mammogram. 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
- [j8]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) - [j7]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) - [j6]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) - [j5]Tobias Heimann, Bram van Ginneken, Martin Styner, Yulia Arzhaeva, Volker Aurich, Christian Bauer, Andreas Beck, Christoph Becker, Reinhard Beichel, György Bekes, Fernando Bello, Gerd Karl Binnig, Horst Bischof, Alexander Bornik, Peter Cashman, Ying Chi, Andrés Cordova, Benoit M. Dawant, Márta Fidrich, Jacob D. Furst, Daisuke Furukawa, Lars Grenacher, Joachim Hornegger, Dagmar Kainmüller, Richard Kitney, Hidefumi Kobatake, Hans Lamecker, Thomas Lange, Jeongjin Lee, Brian Lennon, Rui Li, Senhu Li, Hans-Peter Meinzer, Gábor Németh, Daniela Stan Raicu, Anne-Mareike Rau, Eva M. van Rikxoort, Mikaël Rousson, László Ruskó, Kinda Anna Saddi, Günter Schmidt, Dieter Seghers, Akinobu Shimizu, Pieter Slagmolen, Erich Sorantin, Grzegorz Soza, Ruchaneewan Susomboon, Jonathan M. Waite, Andreas Wimmer, Ivo Wolf:
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. 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
- [j4]Joan Peckham, Fatma Mili, Daniela Stan Raicu, Ingrid Russell:
REUs: undergraduate research experiences and funding. J. Comput. Sci. Coll. 23(5): 208-211 (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. 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. 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. Image Processing 2007: 65120S - [c16]William H. Horsthemke, Daniela Stan Raicu:
Organ analysis and classification using principal component and linear discriminant analysis. Image Processing 2007: 65124A - [c15]Mailan Pham, Ruchaneewan Susomboon, Tim Disney, Daniela Raicu, Jacob Furst:
A comparison of texture models for automatic liver segmentation. 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. 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. Image Processing 2006: 61444G - [c8]Roman Lerman, Daniela Stan Raicu, Jacob D. Furst:
Contrast enhancement of soft tissues in computed tomography images. 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, Ioana L. Coman, Daniela Stan:
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
[j21] [j20] [c102] [c101] [c100] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c91] [c90] [c89] [c88] [c87] [i3] [i2] [c86] [c85] [c84] [c83] [j19] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [c75] [c74] [c73] [j18] [c71] [c70] [c69] [c68] [c66] [c65] [c64] [c63] [j15] [c61] [c60] [i1] [c57] [c56] [j14] [c55] [c54] [c53] [j13] [j12] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [j11] [j10] [c41] [c40] [j9] [c39] [c38] [c37] [c36] [c35] [c34] [c32] [c31] [c30] [c29] [c28] [j8] [j7] [j6] [j5] [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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