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Publications and Patents

Biomedical Imaging

 

Books and Edited Volumes

  •   J. Rittscher and R. T. Whitaker, Medical Image Analysis Journal, Special Issue on Microscopic Image Analysis, February 2009   [MedIA]
  • J. Rittscher, R. Machiraju, and S. T. C. Wong (Editors), Microscopic Image Analysis for Life Science Applications, Artech House, ISBN 978-1-59693-236-4, 2008 (19 chapters, 489 pages) [web]
  •   D. N. Metaxas, R. T. Whitaker, J. Rittscher, and T. B. Sebastian, Proceedings of MICCAI Workshop on Microscopic Image Analysis with Applications in Biology, Copenhagen, Denmark, October 2006  [web]
  • D. Padfield, J. Rittscher, N. Thomas, and B. Roysam, Automated Spatio-Temporal Cell Cycle Phase Analysis Based on Convert GFP Sensors in J. Rittscher, R. Machiraju, und S. T. C. Wong (Editors), Microscopic Image Analysis for Life Science Applications, Artech House, 2008  [web]

Peer-Reviewed Journals

  • M. J. Gerdes, C. J. Sevinsky, A. Sood, S. Adak, M. Bello, A. Can, S. Dinn, R. J. Filkins, M. Larsen, Q. Li, M. C. Montalto, J. Rittscher, J. E. Rothman, Z. Pang, B. D. Sarachan, M. L. Seel, A. Seppo, J. Zhang, and F. Ginty, High-Order Multiplexed Fluorescence Imaging for Quantitative, in Situ Subcellular Analysis of Cancer Tissue, PNAS, 2013 [pubmed]
  • C. C. Bilgin, J. Rittscher, B. Filkins, A. Can, Digitally Adjusting Chromogenic Dye Proportions in Pathology Images, Journal of Microscopy, 2011 [pubmed]
  • D. Padfield, J. Rittscher and B. Roysam, Coupled Minimum-Cost Flow Cell Tracking for High- Throughput Quantitative Analysis, Medical Image Analysis, August 2010 [pubmed]
  • J. Rittscher, Characterization of Biological Processes through Automated Image Analysis (Review), Annual Review of Biomedical Engineering, 12, pages 315-344, August 2010 [web]
  • D. Padfield, J. Rittscher, N. Thomas, and B. Roysam, Spatio-Temporal Cell Cycle Phase Analysis Using Level Set Methods and Fast Marching Methods, Medical Image Analysis, vol. 13, no. 1, pp. 143155, February 2009 [pubmed]

Peer-Reviewed Conference Contributions

  •   A. Santamaria, Y. Huang, and J. Rittscher, Cell Segmentation and Classification Via Unsupervised Shape Ranking, IEEE International Symposium on Biomedical Imaging, San Francisco, 2013   [IEEE Xplore]
  •   X. Liu, S. Iyengar, and J. Rittscher, Monitoring Cardiomyocyte Motion in Real Time Through Image Registration and Time Series Analysis, IEEE International Symposium on Biomedical Imaging, Barcelona, 2012   [IEEE Xplore]
  • D. Margolis, A. Santamaria-Pang, and J. Rittscher, Tissue Segmentation and Classification using Graph-Based Unsupervised Clustering, IEEE International Symposium on Biomedical Imaging, Barcelona, 2012  [IEEE Xplore]
  •   S. Singh, F. Janoos, T. P ecot, E. Caserta, G. Leone, J. Rittscher, and R. Machiraju, Identifying Nuclear Phenotypes using Semi-supervised Metric Learning, The 22nd International Conference on Information Processing in Medical Imaging   [pubmed]
  •   D. Padfield, J. Ritscher and B. Roysam, Quantitative Biological Studies Enabled by Robust Cell Tracking, IEEE International Symposium on Biomedical Imaging (ISBI), Chicago, 2011   [IEEE Xplore]
  •   J. Tu, B. Laflen, X. Liu, M. Bello, J. Rittscher, and P. Tu, LPSM: Fitting Shape Model by Linear Programming, IEEE Conference on Automatic Face and Gesture Recognition, Santa Barbara, 2011   [IEEE Xplore]
  • D. Gao, D. Padfield, J. Rittscher, R. McKay, Automated Training Data Generation for Microscopy Focus Classification, International Conference on Medical Image Computing and Computer Assisted Intervention, Beijing, 2010 [pubmed]
  • S. Singh, S. Raman, E. Caserta, G. Leone, M. Ostrowski, J. Rittscher, and R. Machiraju, Analysis of Spatial Variation of Nuclear Morphology in Tissue Microenvironments, IEEE International Symposium on Biomedical Imaging, Rotterdam, NL, 2010 [IEEE Xplore]
  •   S. Singh, S. Raman, J. Rittscher, and R. Machiraju, Segmentation Evaluation for Fluorescence Microscopy Images of Biological Objects, 4th Workshop on Microscopic Image Analysis with Applications in Biology, Bethesda, MD, 2009  [pdf]
  •   D. Padfield, J. Rittscher, and B. Roysam, Coupled Minimum-Cost Flow Cell Tracking, Information Processing in Medical Imaging, Williamsburg, VA, 2009  [pubmed]
  •   D. Padfield, J. Rittscher, and B. Roysam, Defocus and Low CNR Detection for Cell Tracking Applications, 3rd MICCAI Workshop on Microscopic Image Analysis with Applications in Biology, New York, NY, September, 2008  [miaab]
  •   K. Mosaliganti, S. Singh, S. Naidu, J. Rittscher, R. Bhotika, R. Machiraju, K. Huang, and G. Leone, Estimating Intensity Bias Fields in Confocal Images Showing Salient Cellular Arrangements, 3rd MIC- CAI Workshop on Microscopic Image Analysis with Applications in Biology, New York, NY, September, 2008  [pdf]
  •   D. Padfield, J. Rittscher, and B. Roysam, Spatio-Temporal Cell Segmentation and Tracking for Automated Screening, IEEE International Symposium on Biomedical Imaging, Paris, France, 2008   [IEEE Xplore]
  •   T. Sebastian, J. Rittscher, D. Nelson, and S. Abbot, Automatic Characterization of In Vitro Cardiomyocyte Motion, 2nd Workshop on Microscopic Image Analysis with Applications in Biology, Piscataway, NJ, 2007  [pdf
  • D. Padfield, J. Rittscher, N. Thomas, and B. Roysam, Spatio-temporal Cell Cycle Phase Analysis Using Level Sets and Fast Marching Methods, MICCAI Workshop on Microscopic Image Analysis with Applications in Biology, Copenhagen, 2006 [pdf]
  •   D. Padfield, J. Rittscher, T. Sebastian, N. Thomas, and B. Roysam, Spatio-temporal Cell Cycle Analysis Using 3D Level Set Segmentation of Unstained Confocal Fluorescence Images, IEEE International Symposium on Biomedical Imaging, Arlington, USA, 2006   [IEEE Xplore]
  •   T. Sebastian, J. Rittscher, and L. Yu, Computing Phagocytosis Index for High-Throughput Applications, IEEE International Symposium on Biomedical Imaging, Arlington, USA, 2006   [IEEE Xplore]

Other Publications

  • Rittscher, D. Padfield, A. Santamaria, J. Tu, A. Can, M. Bello, D. Gao, A. Sood, M. Gerdes, and F. Ginty, Methods and Algorithms for Extracting High-Content Signatures from Cells, Tissues and Model Organisms, Special session on Current challenges in image analysis for high-throughput microscopy at IEEE International Symposium on Biomedical Imaging (ISBI), March 2011  [IEEE Xplore]  
  •     D. Padfield, J. Rittscher, N. Thomas, and B. Roysam, Validation Methods for Cell Cycle Analysis Algorithms in Confocal Fluorescence Images, IEEE/NLM Life Science Systems & Applications Workshop, July 2006, Bethesda, MD     [IEEE Xplore]  

Patents

  • USPTO Nr. 8,508,588 Methods and systems identifying well wall boundaries of microplates [uspto]
  • USPTO Nr. 7,940,978 Automatic characterization of cellular motion [uspto]
  • USPTO Nr. 7,817,841 Time-lapse cell cycle analysis of unstained nuclei [uspto]
  • USPTO Pub. App. No. 20130287283 Systems and method for performing quality review scoring of biomarkers and image analysis methods for biological tissue [google patents]
  • USPTO Pub. App. No. 20120275563 System and method for orienting and X-ray detector [google patents]
  • USPTO Pub. App. No. 20110075914 System and method for the quantitative assessment of digital histology images [google patents]
  • USPTO Pub. App. No. 20110069905 System and method for detecting and eliminating one or more defocused or low contrast-to-noise ratio images [google patents]
  • USPTO Pub. App. No. 20110026803 Methods and system for digitally enhancing an image of a stained material [google patents]
  • USPTO Pub. App. No 20100119127 Systems and methods for automated extraction of high-content information from whole organisms [google patents]
  • USPTO Pub. App. No. 20100119119 Automated systems and methods for screening zebrafish [google patents]
  • USPTO Pub. App. No. 20100104513 Method and system for dye assessment [google patents]
  • USPTO Pub. App. No. 20090238457 Method and system for automated segmentation of dense cell populations [google patents]

Computer Vision

Book Chapters

  • J. Rittscher, A. Blake, A. Hoogs, and G. Stein, Mathematical Modeling of Animate and Intentional Motion, in The Neuroscience of Social Interaction - Decoding, imitating and influencing the actions of others, C. Frith and D. Wolpert, Oxford University Press, 2004 [amazon]
  • T. Kelliher, J. Rittscher, and P. H. Tu, Finger and Palm Prints, in J. Payne-James, R. Byard, T. Corey and C. Henderson, Encyclopedia of Forensic and Legal Medicine, Academic Press, 2004 [ScienceDirect]
  • P. H. Tu, J. Rittscher, and T. Kelliher, Fingerprint Challenges, in J. Payne-James, R. Byard, T. Corey and C. Henderson, Encyclopedia of Forensic and Legal Medicine, Academic Press, 2004 [ScienceDirect]

Peer-Reviewed Journals

  • G. Doretto, T. Sebastian, P. Tu and J. Rittscher, T., Tu, P., Appearance-based person re-identification in camera networks: Problem overview and current approaches, Journal of Ambient Intelligence and Humanized Computing, 2011 [pdf]
  • J. Rittscher, A. Blake, A. Hoogs, and G. Stein, Mathematical Modeling of Animate and Intentional Motion, Philosophical Transactions: Biological Sciences, 358(1431), pages 475-490, The Royal Society, London, UK, April 2003 [web]
  • J. Rittscher, A. Blake, and S. Roberts, Towards the Automatic Analysis of Complex Human Body Motion, Image and Vision Computing, 20(12), pages 905-916, December 2002 [source]
  • J. Kato, T. Watanabe, S. Joga, J. Rittscher, and A. Blake, An HMM-based Segmentation Method for Traffic Monitoring Movies, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(9), pages 1291-1296, September 2002 [pdf]
  • B. North, A. Blake, M. Isard, and J. Rittscher, Learning and Classification of Complex Dynamics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(9), pages 1016 - 1034, September 2000 [pdf]

Peer-Reviewed Conference Contributions

  •   J. Tu, B. Laflen, X. Liu, M. Bello, J. Rittscher, and P. Tu, LPSM: Fitting Shape Model by Linear Programming, IEEE Conference on Automatic Face and Gesture Recognition, Santa Barbara, 2011   [IEEE Xplore]
  • S.-N. Lim, G. Doretto and J. Rittscher, Object Constellations: Scalable, Simultaneous Detection and Recognition of Multiple Specific Objects, 11th European Conference on Computer Vision, ECCV Workshop on Vision for Cognitive Tasks, Crete, 2010 [pdf]
  •   X. Wang, G. Doretto, T.B. Sebastian, J. Rittscher, and P.H. Tu, Shape and Appearance Context Modeling, IEEE International Conference on Computer Vision, 2007   [source]
  •   N. Gheissari, T. Sebastian, P.H. Tu, J. Rittscher, and R. Hartley, Person Reidentification Using Spatiotemporal Appearance, IEEE Computer Vision and Pattern Recognition, 2006   [IEEE Xplore]
  •   X. Liu, T. Chen, and J. Rittscher, Optimal Pose for Face Recognition, IEEE Conference on Computer Vision and Pattern Recognition, 2006   [IEEE Xplore]
  •   X. Liu, P.H. Tu, J. Rittscher, A. Perera, and N. Krahnstoever, Detecting and Counting People in Surveillance Applications, IEEE Conference on Advanced Video and Signal Based Surveillance, Como, Italy, 2005  [IEEE Xplore]
  •   J. Rittscher, P.H. Tu, and N. Krahnstoever, Simultaneous Estimation of Segmentation and Shape, IEEE Conference on Computer Vision and Pattern Recognition, San Diego, 2005  [IEEE Xplore]
  •   J. Rittscher, N. Krahnstoever, and L. Galup, Multi-Target Tracking Using Hybrid Particle Filtering, IEEE Workshops on Applications of Computer Vision WACV, Breckenridge, 2005  [IEEE Xplore]
  •   N. Krahnstoever, K. Chean, J. Rittscher, T. Tomlinson, and P. H. Tu, Activity Recognition using Visual Tracking and RFID, IEEE Workshops on Applications of Computer Vision (WACV), Breckenridge, 2005   [IEEE Xplore]
  •   N. Krahnstoever, T. Kelliher, and J. Rittscher, Obtaining Pareto Optimal Performance of Visual Surveillance Algorithms, IEEE International Workshops on Performance Evaluation of Tracking and Surveillance (PETS), Breckenridge, 2005
  •   P. H. Tu and J. Rittscher, Crowd Segmentation through Emergent Labeling, 2nd ECCV Workshop on Statistical Methods in Video Processing, Prague, 2004   [Springer]
  •   A. Hoogs, J. Rittscher, G. Stein, and J. Schmiederer, Video Content Annotation using Visual Analysis and Large Semantic Knowledgebase, IEEE Conference on Computer Vision and Pattern Recognition, 2003   [IEEE Xplore]
  •   G. Stein, J. Rittscher, and A. Hoogs, Enabling Video Annotation using a Semantic Database Extended with Visual Knowledge, IEEE International Conference on Multimedia and Expo, 2003   [IEEE Xplore]
  •   P. Tu, J. Rittscher, and T. Kelliher, Site Calibration for Large Indoor Scenes, IEEE International Conference on Advanced Video and Signal Based Surveillance, Miami, 2003  [IEEE Xplore
  •   S. Sullivan and J. Rittscher, Guiding Random Particles by Deterministic Search, 8th International Conference on Computer Vision, Vancouver, Canada, 2001   [IEEE Xplore]
  •   J. Rittscher and S. Sullivan, An Integral Criterion for Detecting Boundary Edges and Textured Regions, 15th International Conference on Pattern Recognition, Barcelona, Spain, 2000  [IEEE Xplore
  •   J. Rittscher, J. Kato, S. Joga, and A. Blake, A Probabilistic Background Model for Tracking, 6th European Conference on Computer Vision, Dublin, Ireland, 2000   [pdf]
  •   J. Sullivan, A. Blake, and J. Rittscher, Statistical Foreground Modelling for Object Localisation, 6th European Conference on Computer Vision, Dublin, Ireland, 2000   [Springer]
  •   J. Rittscher and A. Blake, Classification of Human Body Motion, 7th International Conference on Computer Vision, Kerkyra, Greece, 1999  [pdf]

Other Publications

  •     P.H. Tu, F. Wheeler, N. Krahnstoever, T. Sebastian, J. Rittscher, X. Liu, A. Perera, and G. Doretto, Surveillance video analytics for large camera networks, SPIE Letters, 2007     [spie]  
  •     P.H. Tu, G. Doretto, N.O. Krahnstoever, A.A.G. Perera, F.W. Wheeler, X. Liu, J. Rittscher, T.B. Sebastian, T. Yu, and K.G. Harding, K. G., An intelligent video framework for homeland protection. In Proceedings of SPIE Defense and Security Symposium - Unattended Ground, Sea, and Air Sensor Technologies and Applications IX, Orlando, FL, USA, April 9 - 13, 2007. (invited submission)     [CiteSeer]  
  •     S. Luckhaus, K. Räwer and J. Rittscher, A new Γ-convergent approximation to the Mumford-Shah functional. Preprint Nr. 517, Sonderforschungsbereich 256, Universität Bonn

Patents

  • USPTO Nr. 8,457,406 Identifying descriptor for person and object in an image [uspto]
  • USPTO Nr. 8,452,096 Identifying descriptor for person or object in an image [uspto]
  • USPTO Nr. 8,355,576 Method and System for crowd segmentation [uspto]
  • USPTO Nr. 8,295,543 Device and method for detecting targets in images based on user-defined classifiers [uspto]
  • USPTO Nr. 8,233,662 Method and system for detecting signal color from a moving video platform [uspto]
  • USPTO Nr. 8,184,915 Device and method for fast computation of region based image features [uspto]
  • USPTO Nr. 8,165,397 Identifying descriptor for person or object in an image [uspto]
  • USPTO Nr. 8,154,600 Method and system for distributed multiple target tracking [uspto]
  • USPTO Nr. 7,885,429 Standoff detection systems and methods [uspto]
  • USPTO Nr. 7,711,146 Method and system for performing image re-identification [uspto]
  • USPTO Nr. 7,596,241 System and method for automatic person counting and detection of specific events [uspto]
  • USPTO Nr. 7,356,425 Method and system for camera autocalibration [uspto]
  • USPTO Nr. 7,049,965 Surveillance systems and methods [uspto]
  • USPTO Nr. 6,911,907 System and method of providing security for a site [uspto]
  • USPTO Nr. 6,853,936 Method and system for calibrating multiple cameras with potentially non-overlapping fields of view [uspto]
  • USPTO Pub. App. No. 20110051999 Device and method for detecting targets in images based on user-defined classifiers [google patents]
  • USPTO Pub. App. No. 20090310862 Method and system for crowd segmentation [google patents]
  • USPTO Pub. App. No. 20090034791 Image processing for person and object re-identification [google patents]
  • USPTO Pub. App. No. 20090238457 Method and system for automated segmentation of dense cell populations [google patents]
  • USPTO Pub. App. No. 20080291272 Method and System for remote estimation of motion parameters [google patents]
  • USPTO Pub. App. No. 20080259163 Method and system for distributed multiple target tracking [google patents]
  • USPTO Pub. App. No. 20080187220 Device and method for fast computation of region based image [google patents]
  • USPTO Pub. App. No. 20060120571 System and method for passive face recognition [google patents]
  • USPTO Pub. App. No. 20060045310 System and method for tracking articulated body motion [google patents]
  • USPTO Pub. App. No. 20050254546 System and method for segmenting crowded environments into individual objects [google patents]
  • USPTO Pub. App. No. 20050102183 Monitoring system and method based on information prior to the point of sale [google patents]
  • USPTO Pub. App. No. 20050068171 Wearable security system and method [google patents]