and Activity Modeling for Monitoring Surgical Procedures

[1]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[2]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[3]  Bernt Schiele,et al.  Scalable Recognition of Daily Activities with Wearable Sensors , 2007, LoCA.

[4]  Stuart J. Russell,et al.  Dynamic bayesian networks: representation, inference and learning , 2002 .

[5]  Nassir Navab,et al.  Recovery of Surgical Workflow: a Model-based Approach , 2007 .

[6]  Jakob E. Bardram,et al.  Applications of context-aware computing in hospital work: examples and design principles , 2004, SAC '04.

[7]  James W. Davis,et al.  The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Maja J. Mataric,et al.  A spatio-temporal extension to Isomap nonlinear dimension reduction , 2004, ICML.

[9]  Alex Macario,et al.  Initial clinical evaluation of a handheld device for detecting retained surgical gauze sponges using radiofrequency identification technology. , 2006, Archives of surgery.

[10]  Kevin Cleary,et al.  OR 2020: the operating room of the future. , 2004, Journal of laparoendoscopic & advanced surgical techniques. Part A.

[11]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[12]  T. Gasser,et al.  Alignment of curves by dynamic time warping , 1997 .

[13]  H. Feußner,et al.  Technik der laparoskopischen Cholezystektomie , 1991, Langenbecks Archiv für Chirurgie.

[14]  Kevin P. Murphy,et al.  Learning the Structure of Dynamic Probabilistic Networks , 1998, UAI.

[15]  Oliver Brdiczka,et al.  Learning Situation Models for Providing Context-Aware Services , 2007, HCI.

[16]  Irfan A. Essa,et al.  Discovering Characteristic Actions from On-Body Sensor Data , 2006, 2006 10th IEEE International Symposium on Wearable Computers.

[17]  Alex Pentland,et al.  Task-Specific Gesture Analysis in Real-Time Using Interpolated Views , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Matthai Philipose,et al.  Unsupervised Activity Recognition Using Automatically Mined Common Sense , 2005, AAAI.

[19]  Nassir Navab,et al.  On-line Recognition of Surgical Activity for Monitoring in the Operating Room , 2008, AAAI.

[20]  J.M. Van Thong,et al.  BioStream: a system architecture for real-time processing of physiological signals , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[21]  Claudio S. Pinhanez,et al.  Intelligent Studios Modeling Space and Action to Control TV Cameras , 1997, Appl. Artif. Intell..

[22]  Ken Masamune,et al.  Development and evaluation of the second version of scrub nurse robot (SNR) for endoscopic and laparoscopic surgery , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Michael W. Vannier,et al.  The operating room and the need for an IT infrastructure and standards , 2006, International Journal of Computer Assisted Radiology and Surgery.

[24]  Ramakant Nevatia,et al.  Single View Human Action Recognition using Key Pose Matching and Viterbi Path Searching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Heinz U. Lemke,et al.  Specification and design of a therapy imaging and model management system (TIMMS) , 2007, SPIE Medical Imaging.

[26]  Irfan A. Essa,et al.  Structure from Statistics - Unsupervised Activity Analysis using Suffix Trees , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[27]  Todd Andrew Stephenson,et al.  An Introduction to Bayesian Network Theory and Usage , 2000 .

[28]  Shahram Payandeh,et al.  Task and Motion Analyses in Endoscopic Surgery , 1996, Dynamic Systems and Control.

[29]  J.L. Baron.  Experience with 3D optical flow on gated MRI cardiac datasets , 2004, First Canadian Conference on Computer and Robot Vision, 2004. Proceedings..

[30]  Marie T Egan,et al.  Auto Identification Technology and Its Impact on Patient Safety in the Operating Room of the Future , 2007, Surgical innovation.

[31]  Ken Masamune,et al.  Scrub nurse robot system-intraoperative motion analysis of a scrub nurse and timed-automata-based model for surgery , 2005, IEEE Transactions on Industrial Electronics.

[32]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[33]  Oliver Burgert,et al.  A general framework for data streaming in the digital operating room , 2008, SPIE Medical Imaging.

[34]  B. Davies.  A review of robotics in surgery , 2000, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[35]  Irfan A. Essa,et al.  Recognizing multitasked activities from video using stochastic context-free grammar , 2002, AAAI/IAAI.

[36]  Nassir Navab,et al.  A Boosted Segmentation Method for Surgical Workflow Analysis , 2007, MICCAI.

[37]  Gaetano Borriello,et al.  A Practical Approach to Recognizing Physical Activities , 2006, Pervasive.

[38]  David Burshtein,et al.  An enhanced dynamic time warping model for improved estimation of DTW parameters , 2003, IEEE Trans. Speech Audio Process..

[39]  Yan Xiao,et al.  An Algorithm for Processing Vital Sign Monitoring Data to Remotely Identify Operating Room Occupancy in Real-Time , 2005, Anesthesia and analgesia.

[40]  Guang-Zhong Yang,et al.  Episode Classification for the Analysis of Tissue/Instrument Interaction with Multiple Visual Cues , 2003, MICCAI.

[41]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[42]  Nassir Navab,et al.  Workflow mining for visualization and analysis of surgeries , 2008, International Journal of Computer Assisted Radiology and Surgery.

[43]  Paul Lukowicz,et al.  Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[44]  Irfan A. Essa,et al.  Learning Temporal Sequence Model from Partially Labeled Data , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[45]  Bernard Gibaud,et al.  Modeling Surgical Procedures for Multimodal Image-Guided Neurosurgery , 2001, MICCAI.

[46]  M. Frecker,et al.  Sequence and task analysis of instrument use in common laparoscopic procedures , 2002, Surgical Endoscopy And Other Interventional Techniques.

[47]  Nassir Navab,et al.  Planning and intraoperative visualization of liver catheterizations: new CTA protocol and 2D-3D registration method. , 2007, Academic radiology.

[48]  Nassir Navab,et al.  Real-Time 3D Reconstruction for Collision Avoidance in Interventional Environments , 2008, MICCAI.

[49]  Nassir Navab,et al.  Automatic feature generation in endoscopic images , 2008, International Journal of Computer Assisted Radiology and Surgery.

[50]  B.-H. Juang,et al.  On the hidden Markov model and dynamic time warping for speech recognition — A unified view , 1984, AT&T Bell Laboratories Technical Journal.

[51]  Vojkan Mihajlovic,et al.  Dynamic Bayesian Networks: A State of the Art , 2001 .

[52]  Matthew Brand,et al.  Discovery and Segmentation of Activities in Video , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[53]  W. Eric L. Grimson,et al.  Unsupervised Activity Perception by Hierarchical Bayesian Models , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[54]  A F Bobick,et al.  Movement, activity and action: the role of knowledge in the perception of motion. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[55]  Yan Xiao,et al.  Advanced Visualization Platform for Surgical Operating Room Coordination: Distributed Video Board System , 2006, Surgical innovation.

[56]  Svetha Venkatesh,et al.  Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[57]  Heinz U. Lemke,et al.  Summary of the white paper of DICOM WG24 'DICOM in Surgery' , 2007, SPIE Medical Imaging.

[58]  Zhibin Jiang,et al.  A Surgical Management Information System Driven by Workflow , 2006, 2006 IEEE International Conference on Service Operations and Logistics, and Informatics.

[59]  Nassir Navab,et al.  Wavelet energy map: A robust support for multi-modal registration of medical images , 2009, CVPR.

[60]  Thomas M. Krummel,et al.  Innovation in Surgery: A Historical Perspective , 2006, Annals of surgery.

[61]  Michael I. Jordan,et al.  Factorial Hidden Markov Models , 1995, Machine Learning.

[62]  Marie T. Egan,et al.  Deliberate Perioperative Systems Design Improves Operating Room Throughput , 2005, Anesthesiology.

[63]  Darius Burschka,et al.  Synchronized Multimodal Recording System for Laparoscopic Minimally Invasive Surgeries , 2009 .

[64]  Shaogang Gong,et al.  Optimising dynamic graphical models for video content analysis , 2008, Comput. Vis. Image Underst..

[65]  Joshua R. Smith,et al.  RFID-based techniques for human-activity detection , 2005, Commun. ACM.

[66]  G. J. Klein,et al.  A 3D optical flow approach to addition of deformable PET volumes , 1997, Proceedings IEEE Nonrigid and Articulated Motion Workshop.

[67]  François Pugin,et al.  Single Port Access Laparoscopic Cholecystectomy (with video) , 2009, World Journal of Surgery.

[68]  Emmanuel Jeannot,et al.  Messages Scheduling for Parallel Data Redistribution between Clusters , 2006, IEEE Transactions on Parallel and Distributed Systems.

[69]  Richard Szeliski,et al.  Rapid octree construction from image sequences , 1993 .

[70]  Peter Fu-Ming Hu,et al.  Real-Time Identification of Operating Room State from Video , 2007, AAAI.

[71]  Andreas Krause,et al.  Unsupervised, dynamic identification of physiological and activity context in wearable computing , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[72]  Albrecht Schmidt,et al.  Multi-sensor Activity Context Detection for Wearable Computing , 2003, EUSAI.

[73]  A. Darzi,et al.  HMM assessment of quality of movement trajectory in laparoscopic surgery , 2007, Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention.

[74]  Gregory D. Hager,et al.  Towards automatic skill evaluation: detection and segmentation of robot-assisted surgical motions. , 2006 .

[75]  Robert E. Mercer,et al.  3D regularized velocity from 3D Doppler radial velocity , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[76]  P. A. Taylor,et al.  Synchronization of batch trajectories using dynamic time warping , 1998 .

[77]  Nassir Navab,et al.  Action- and Workflow-Driven Augmented Reality for Computer-Aided Medical Procedures , 2007, IEEE Computer Graphics and Applications.

[78]  G. Berci,et al.  The operating room of the future: what, when and why? , 2003, Surgical Endoscopy And Other Interventional Techniques.

[79]  D. Oleynikov,et al.  Radio frequency identification (RFID) applied to surgical sponges , 2007, Surgical Endoscopy.

[80]  Eamonn J. Keogh,et al.  Exact indexing of dynamic time warping , 2002, Knowledge and Information Systems.

[81]  Irfan A. Essa,et al.  Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning , 2007, AAAI.

[82]  Adam Prügel-Bennett,et al.  Evolving the structure of hidden Markov models , 2006, IEEE Transactions on Evolutionary Computation.

[83]  Nassir Navab,et al.  Workflow monitoring based on 3D motion features , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[84]  Richard Szeliski,et al.  A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[85]  Jesús Favela,et al.  Activity Recognition for the Smart Hospital , 2008, IEEE Intelligent Systems.

[86]  Yuji Iwahori,et al.  Robust Background Subtraction for Quick Illumination Changes , 2006, PSIVT.

[87]  Shih-Fu Chang,et al.  Structure analysis of soccer video with domain knowledge and hidden Markov models , 2004, Pattern Recognit. Lett..

[88]  Nassir Navab,et al.  Recovery of Surgical Workflow Without Explicit Models , 2006, MICCAI.

[89]  Nassir Navab,et al.  Modeling and Online Recognition of Surgical Phases Using Hidden Markov Models , 2008, MICCAI.

[90]  L. MacKenzie,et al.  Hierarchical decomposition of laparoscopic surgery: a human factors approach to investigating the operating room environment , 2001, Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy.

[91]  Daniel Weinland,et al.  Action Representation and Recognition , 2008 .

[92]  Tomás Svoboda,et al.  A Convenient Multicamera Self-Calibration for Virtual Environments , 2005, Presence: Teleoperators & Virtual Environments.

[93]  Mike Y. Chen,et al.  Tracking Free-Weight Exercises , 2007, UbiComp.

[94]  Rémi Ronfard,et al.  Free viewpoint action recognition using motion history volumes , 2006, Comput. Vis. Image Underst..

[95]  Konrad Tollmar,et al.  Activity Zones for Context-Aware Computing , 2003, UbiComp.

[96]  Warren S. Sandberg,et al.  A computerized perioperative data integration and display system , 2007, International Journal of Computer Assisted Radiology and Surgery.

[97]  Shih-Fu Chang,et al.  Unsupervised discovery of multilevel statistical video structures using hierarchical hidden Markov models , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[98]  Rémi Ronfard,et al.  Action Recognition from Arbitrary Views using 3D Exemplars , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[99]  Alex Pentland,et al.  Coupled hidden Markov models for complex action recognition , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[100]  A. Darzi,et al.  Assessing operative skill , 1999, BMJ.

[101]  François Brémond,et al.  Automatic Video Interpretation: A Novel Algorithm for Temporal Scenario Recognition , 2003, IJCAI.

[102]  Steven C. Horii,et al.  Workflow in the operating room: review of Arrowhead 2004 seminar on imaging and informatics (Invited Paper) , 2005, SPIE Medical Imaging.

[103]  Eamonn J. Keogh,et al.  Clustering of time-series subsequences is meaningless: implications for previous and future research , 2004, Knowledge and Information Systems.

[104]  Thomas Neumuth,et al.  Linking Top-Level Ontologies and Surgical Workflows , 2006 .

[105]  Gero Strauß,et al.  Acquisition of Process Descriptions from Surgical Interventions , 2006, DEXA.

[106]  Thomas Neumuth,et al.  Visualization Options for Surgical Workflows , 2006 .

[107]  L. Morgenstern.  Carl Langenbuch and the first cholecystectomy , 2006, Surgical Endoscopy.

[108]  Nassir Navab,et al.  Synchronizing 3D movements for quantitative comparison and simultaneous visualization of actions , 2005, Fourth IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR'05).

[109]  M. Ostendorf,et al.  Maximum likelihood successive state splitting , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[110]  R. Satava.  The Operating Room of the Future: Observations and Commentary , 2003, Seminars in laparoscopic surgery.

[111]  Neil A. Thacker,et al.  Tutorial: Computing 2D and 3D Optical Flow. , 2004 .

[112]  Jesus J. Caban,et al.  Radio Frequency Identification Systems Technology in the Surgical Setting , 2006, Surgical innovation.

[113]  John Kenneth Salisbury,et al.  The Intuitive/sup TM/ telesurgery system: overview and application , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[114]  Didier Mutter,et al.  Surgery without scars: report of transluminal cholecystectomy in a human being. , 2007, Archives of surgery.

[115]  Andreas Stolcke,et al.  Best-first Model Merging for Hidden Markov Model Induction , 1994, ArXiv.

[116]  Blake Hannaford,et al.  Automated Tool Handling for the Trauma Pod Surgical Robot , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[117]  Thomas Neumuth,et al.  Deriving DICOM surgical extensions from surgical workflows , 2007, SPIE Medical Imaging.

[118]  A. Laurentini,et al.  The Visual Hull Concept for Silhouette-Based Image Understanding , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[119]  Yulun Wang,et al.  Robotic surgery - the transatlantic case , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[120]  Cordelia Schmid,et al.  A Spatio-Temporal Descriptor Based on 3D-Gradients , 2008, BMVC.

[121]  Pierre Jannin,et al.  Surgical models for computer-assisted neurosurgery , 2007, NeuroImage.

[122]  Blake Hannaford,et al.  Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model , 2006, IEEE Transactions on Biomedical Engineering.

[123]  Luís A. Castro,et al.  Activity Recognition for Context-aware Hospital Applications: Issues and Opportunities for the Deployment of Pervasive Networks , 2007, Mob. Networks Appl..

[124]  Irfan A. Essa,et al.  Exploiting human actions and object context for recognition tasks , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[125]  Walter Daelemans,et al.  Automatic discovery of workflow models from hospital data , 2001 .

[126]  Jitendra Malik,et al.  Recognizing action at a distance , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[127]  N. Navab,et al.  Advanced Medical Displays: A Literature Review of Augmented Reality , 2008, Journal of Display Technology.

[128]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[129]  David A. Forsyth,et al.  Searching for Complex Human Activities with No Visual Examples , 2008, International Journal of Computer Vision.

[130]  T. Peters.  Image-guidance for surgical procedures , 2006, Physics in medicine and biology.

[131]  H. Feußner.  The Operating Room of the Future: A View from Europe , 2003, Seminars in laparoscopic surgery.

[132]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[133]  R. M. Satava,et al.  Telesurgery, robotics, and the future of telemedicine , 2005, European Surgery.

[134]  Emmanuel Jeannot,et al.  Messages Scheduling for Data Redistribution between Clusters , 2003, PPAM.

[135]  Mubarak Shah,et al.  Learning 4D action feature models for arbitrary view action recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[136]  Nassir Navab,et al.  Efficient visual hull computation for real-time 3D reconstruction using CUDA , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[137]  Jake K. Aggarwal,et al.  Human motion analysis: a review , 1997, Proceedings IEEE Nonrigid and Articulated Motion Workshop.

[138]  José Bravo,et al.  Identification technologies to support Alzheimer contexts , 2008, PETRA '08.

[139]  C. Zornig,et al.  Scarless cholecystectomy with combined transvaginal and transumbilical approach in a series of 20 patients , 2008, Surgical Endoscopy.

[140]  Rüdiger Dillmann,et al.  Recognition of risk situations based on endoscopic instrument tracking and knowledge based situation modeling , 2008, SPIE Medical Imaging.

[141]  W. Eric L. Grimson,et al.  Using adaptive tracking to classify and monitor activities in a site , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[142]  Eric Horvitz,et al.  Layered representations for learning and inferring office activity from multiple sensory channels , 2004, Comput. Vis. Image Underst..

[143]  Andrew W. Moore,et al.  Fast State Discovery for HMM Model Selection and Learning , 2007, AISTATS.

[144]  Joseph A. Paradiso,et al.  Shoe-integrated sensor system for wireless gait analysis and real-time feedback , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[145]  Guang-Zhong Yang,et al.  Eye-Gaze Driven Surgical Workflow Segmentation , 2007, MICCAI.

[146]  S. Chiba,et al.  Dynamic programming algorithm optimization for spoken word recognition , 1978 .

[147]  Nassir Navab,et al.  New CTA Protocol and 2D-3D Registration Method for Liver Catheterization , 2006, MICCAI.

[148]  Geoffrey G. Zhang,et al.  Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data , 2008, Journal of applied clinical medical physics.

[149]  Douglas O. Olsen,et al.  Historical Overview and Indications for Cholecystectomy , 2004 .

[150]  David C. Minnen,et al.  Propagation networks for recognition of partially ordered sequential action , 2004, CVPR 2004.