A computer analysis of structures in image sequences: methods and applications

Transcription

1 A computer analysis of structures in image sequences: methods and applications João Manuel R. S. Tavares Mathematical Aspects of Imaging, Modeling and Visualization in Multiscale Biology March 31 April 4, 2009, The University of Texas at Austin, USA

2 Outline Presentation Introduction Tasks and Applications Segmentation Tracking Matching, Registration and Morphing 3D Reconstruction Research Projects & PhD Thesis Scientific Events and Publications Research Team Conclusions and Future Work 2

3 Presentation

4 Presentation Assistant Professor at Faculty of Engineering of University of Porto (FEUP) / Department of Mechanical Engineering and Industrial Management Senior Research and Projects Coordinator of the Optics and Experimental Mechanics Lab (LOME) of the Institute of Mechanical Engineering and Industrial Management (INEGI) PhD and MSc degrees in Electrical and Computer Engineering from FEUP in 2001 and 1995, respectively BSc degree in Mechanical Engineering from FEUP in 1992 Research Areas: Image Processing and Analysis, Human- Computer Interaction, Product Development 4

5 FEUP: Identity With more than 80 years of history, FEUP is the largest school of Universidade do Porto; since 2000, FEUP has moved to a brand new campus, just outside the city centre, in eastern Porto, Portugal 5

6 FEUP: PORTO World heritage 6

7 FEUP: Some Numbers Courses 3 undergraduate courses (1st Cycle), 2 of which are in cooperation 9 integrated master in engineering (1st + 2nd Cyles) 8 MSc programmes (2nd Cycle) 18 PhD programmes (3rd Cycle) Academic community full time teaching and research staff 432 FTE 77% Doctorate administrative and technical staff 231 staff 800 other contracts undergraduate students (1st + 2nd cycles) 5844 master and doctorate students Scientific production 1.1 ISI paper / permanent staff / year 41 active or pending patents and brands 18 spin-offs 7

8 INEGI: Identity The Institute of Mechanical Engineering and Industrial Management (INEGI) is an interface Institution between University and Industry, founded in 1986 INEGI is oriented to activities of Research and Development (R&D), Innovation and Technology Transfer INEGI has two R&D units financed and evaluated by the Fundação para a Ciência e a Tecnologia (FCT): the Experimental Mechanics and New Materials Unit (EXPMAT) and the New Technologies and Advanced Production Processes Unit (NOTEPAP) The two research units that are part of the Associated Lab for Energy, Transports and Aeronautics (LAETA), founded in 2006 and member of the Portuguese Council of the Associated Labs (CLA) 8

9 INEGI: Identity The Experimental Mechanics and New Materials Unit (EXPMAT) is supported by a staff of more than 60 researchers (31 of which have a PhD degree) EXPMAT is involved in partnership with more than 30 foreign companies, universities and other research organizations in many research projects under European or more World-wide programs Recently, EXPMAT has been developing considerable research in Bioengineering, Biomedical and Computational Vision fields 9

10 INEGI: Identity INEGI is located in the FEUP Campus since

11 Introduction: Computer Analysis of Structures in Image Sequences

12 Computer Analysis of Structures in Image Sequences The sensorial vision system has raised importance for numerous living organisms Making possible the processing of information of the most basic sort, as to check the existence of obstacles, or of the most complex kind, as the tracking and analysis of objects movement Common operations are: identification of objects (segmentation), tracking of movement (tracking and analysis), objects matching and registration (matching and registration), reconstruction of 3D shapes from images (3D reconstruction) 12

13 Computer Analysis of Structures in Image Sequences The researchers of the Computational Vision domain aim the development of computational algorithms to accomplish the operations and tasks performed by the (awfully complex) human s vision system in a full or semi-automatic manner Original images Computational 3D model built: voxelized and poligonized Azevedo et al. (2007), 3D Volumetric Reconstruction and Characterization of Objects from Uncalibrated Images, VIIP 2007, Spain,

14 Computer Analysis of Structures in Image Sequences Examples of common tasks involved in the computer analysis of structures in images are: noise removal, geometric correction, data compression, segmentation (2D/3D), tracking and analysis of movement (2D/3D), matching and registration (2D/3D) and 3D reconstruction Domains where algorithms of computer analysis of structures in images are frequently used: Medicine, Biology, Industry, Engineering, Biomechanics, Virtual Reality, etc. 14

15 Tasks and Applications: Structures Segmentation

16 Structures Segmentation It is intended to identify in a full automatically, or semiautomatically, way the structures (2D/3D) presented in an image or along image sequences The most common methodologies used are based on statistical, geometric or physical modeling It is one of the most usual operations involved in the computer analysis of structures in images, being frequently the first important considered task Common problems: noise, low resolution, reduced contrast, shapes not previously known, partial occlusions, multiple structures presented, etc. 16

17 Structures Segmentation Example: contours segmentation in dynamic pedobarography (Otsu method) lamp pressure opaque layer transparent layer reflected light glass lamp contact layer + glass mirror camera Original images After segmentation Bastos & Tavares (2004), Improvement of Modal Matching Image Objects in Dynamic Pedobarography using Optimization Techniques, Lecture Notes in Computer Science 3179:

18 Structures Segmentation Example: analysis of the damage in composite materials (binarization and region analysis) Original image After segmentation Damage area obtained Marques et al. (in press), Composites Science and Technology, DOI: /j.compscitech Measures obtained 18

19 Structures Segmentation Example: analysis of materials microstructures (using neural networks) Original images After segmentation Albuquerque et al. (2008), A New Solution for Automatic Microstructures Analysis from Images Based on a Backpropagation Artificial Neural Network, Nondestructive Testing and Evaluation 23(4):

20 Structures Segmentation Example: control of a servomechanism by gestual language (orientation histograms) Running mode Command image acquisition Conversion for 256 gray levels Comparison of the images orientation histogram vector with the stored vectors of the preset orders images Orders images acquisition (one by one) Conversion for 256 gray levels Learning mode Orders orientation histogram vectors initialization (stored in memory) Associated command order Tavares et al. (2005), Control a 2-Axis Servomechanism by Gesture Recognition using a Generic WebCam, International Journal of Advanced Robotic Systems 2(1):

21 Structures Segmentation Example: detention of tumors in mammography images (Hough transform) Original image After segmentation Chagas et al. (2007), An Application of Hough Transform to Identify Breast Cancer in Images, VIPimage 2007, Portugal,

22 Structures Segmentation Example: image identification (image template matching) Original image fft ift fft Template image max CC ift ( ) 2D CC ( ) ift 3D CC Carvalho & Tavares (2005), Metodologias para identificação de faces em imagens: Introdução e exemplos de resultados, CMNI 2005, España 22

23 Structures Segmentation Example: segmentation using deformable geometric templates Original image and associated energy fields Segmentation of the iris using a deformable template (a circle) Carvalho & Tavares (2006), Two Methodologies for Iris Detection and Location in Face Images, CompIMAGE 2006, Portugal, Carvalho & Tavares (2007), Eye detection using a deformable template in static images, VipIMAGE 2007, Portugal, Segmentation of an eye using an deformable template 23

24 Structures Segmentation Example: segmentation of faces in images using statistical models for the skin Samples used to build the statistical model Probably function used Original image and segmentation obtained Carvalho & Tavares (2005), Metodologias para identificação de faces em imagens: Introdução e exemplos de resultados, CMNI 2005, España 24

25 Structures Segmentation Example: background/foreground scene segmentation using statistical models Background subtraction method Foreground object detection method Vasconcelos & Tavares (2008), Image Segmentation for Human Motion Analysis: Methods and Applications, WCCM8 / ECCOMAS 2008, Italy 25

26 Structures Segmentation Example: segmentation using approaches based on point distributions models (Active Shape Models, Active Appearance Models) Segmentation using Active Shape Models Vasconcelos & Tavares (2006), Methodologies to Build Automatic Point Distribution Models for Faces Represented in Images, CompIMAGE 2006, Portugal,

27 Structures Segmentation Example: segmentation using approaches based on point distributions models (Active Shape Models, Active Appearance Models) Segmentation using an Active Appearance Model Original image Resultant image Vasconcelos & Tavares (2008), Methods to Automatically Built Point Distribution Models for Objects like Hand Palms and Faces Represented in Images, Computer Modeling in Engineering & Sciences 36(3):

28 Structures Segmentation Example: segmentation in the analysis of the vocal tract in speech production (Active Shape Models) Image labeled Original shape Segmentation Vasconcelos et al. (2009), Analysis of Tongue Shape and Motion in Speech Production using Statistical Modeling, 2nd South-East European Conf. on Computational Mechanics, Greece 28

29 Structures Segmentation Example: segmentation using deformable physical models (active contours - snakes) Original image and initial contour Final contour Tavares et al. (in press), Computer Analysis of Objects Movement in Image Sequences: Methods and Applications, International Journal for Computational Vision and Biomechanics 29

30 Structures Segmentation Example: segmentation using deformable physical models (FEM, Lagrange equation) rubber k = 200N/m 14s Original image and initial contour Final contour Gonçalves et al. (2008), Segmentation and Simulation of Objects Represented in Images using Physical Principles, Computer Modeling in Engineering & Sciences 32(1):

31 Structures Segmentation Example: segmentation of medical images using levelsets methods Original image Initial segmentation Final segmentation Perdigão et al. (2005), Geração de modelos de malhas de elementos finitos a partir de imagens médicas 2D, Encontro_1_Biomecânica, Portugal,

32 Structures Segmentation Example: segmentation of medical images using a new computational framework (VC++, OpenCV, ITK) Interface of our platform Ma et al. (2008), Segmentation of Structures in Medical Images: Review and a New Computational Framework, CMBBE2008, Portugal 32

33 Structures Segmentation Example: segmentation of images of the pelvic cavity (using our platform) Region Growing Watershed Geodesic Active Contour Malladi s Algorithm Ma et al. (in press), A Review of Algorithms for Medical Image Segmentation and their Applications to the Female Pelvic Cavity, Computer Methods in Biomechanics and Biomedical Engineering 33

34 Tasks and Applications: Structures Tracking

35 Structures Tracking It is intended to track the movement (and/or the deformation) of structures along image sequences In this area, the methodologies based on block matching and stochastic methods are common Usually, it involves the estimation of the movement involved, the management of the entities being tracked, the analysis of the movement tracked as well as its quantification Usual problems: non-rigid movement, geometric distortions, non-constant illumination conditions, occlusion, noise, multiple structures, etc. 35

36 Structures Tracking Example: contours tracking in dynamic pedobarography (FEM, Modal Analysis) Contours tracking Tavares & Bastos (2005), Improvement of Modal Matching Image Objects in Dynamic Pedobarography using Optimization Techniques, Electronic Letters on Computer Vision and Image Analysis 5(3):

37 Structures Tracking Example: tracking in gait analysis (Kalman, optimization) Prediction Uncertainty Area Measurement Correspondence Result Pinho et al. (2005), Human Movement Tracking and Analysis with Kalman Filtering and Global Optimization Techniques, ICCB 2005, Portugal,

38 Structures Tracking Example: tracking in gait analysis with detention of events (Kalman, optimization) Sousa et al. (2007), Registration between Data from Visual Sensors and Force Platform in Gait Event Detection, ISHF2007, Portugal, Sousa et al. (2007), Selecting Biomechanical Variables for Detect Gait Events using Computational Vision, ICCB 2007, Venuzuela, João Manuel R. S. Tavares A computer analysis of structures in image sequences: methods and applications 38

39 Structures Tracking Example: structures tracking along lengthy image sequences (Kalman, optimization, features management model) (547 frames) Pinho et al. (2005), A Movement Tracking Management Model with Kalman Filtering, Global Optimization Techniques and Mahalanobis Distance, LSCCS, Vol. 4A: Pinho et al. (2007), Efficient Approximation of the Mahalanobis Distance for Tracking with the Kalman Filter, International Journal of Simulation Modelling 6(2):84-92 João Manuel R. S. Tavares A computer analysis of structures in image sequences: methods and applications 39

40 Structures Tracking Our actual goal: Dynamical model(s) - Learning algorithm(s) to estimate the best models parameters Several objects = One dynamical model Large image sequences = One dynamical model 40

41 Tasks and Applications: Structures Matching, Registration and Morphing

42 Structures Matching, Registration and Morphing Matching It is regularly used in the computer analysis of structures in images, for example, to register (align) structures in images, recognize structures, obtain 3D information, analyze the movement tracked, etc. Generally, it is accomplished through the consideration of characteristic invariants, as the curvature, or the displacements in global spaces, as the modal space Common problems: occlusion, non-rigid deformations, high shapes variations, etc. 42

43 Structures Matching, Registration and Morphing Registration It is commonly required to compare structures represented in images acquired in different time instants or according distinct conditions It is essential, for example, in Medicine to follow up the evaluation of patients diseases from images Generally, it is accomplished through the consideration of structures characteristic features, as maximum curvature points, their matching and the estimation of the involved transformation Common problems: key and invariant features not easily identified, occlusion, non-rigid deformations, high shapes variations, etc. 43

44 Structures Matching, Registration and Morphing Morphing (simulation) It is a very used task in Computer Graphics but also very useful in the analysis of structures in images, for example, to estimate the deformation involved between two distinct structures or between two configurations of one structure, to estimate the transitions between two shapes acquired with high temporal gap, etc. Generally, it is accomplished through the consideration of geometric transformations However, when it must be considered the physical behavior of the involved structures, physical methodologies and modeling, as for example FEM, should be employed Common difficulties are related with the estimation of the involved forces and with the properties of the adopted (virtual) material The adequate matching of the structures involved becomes crucial 44

45 Structures Matching Example: matching contours and surfaces in dynamic pedobarography (FEM, Modal Analysis, optimization) Initial contour Final contour Matching found Image of dynamic pedobarography Tavares & Bastos (2005), Improvement of Modal Matching Image Objects in Dynamic Pedobarography using Optimization Techniques, Electronic Letters on Computer Vision and Image Analysis 5(3):

46 Structures Matching Example: matching contours and surfaces in dynamic pedobarography (FEM, Modal Analysis, optimization) Matchings found between iso-contours Matchings found between surfaces Tavares & Bastos (2005), Improvement of Modal Matching Image Objects in Dynamic Pedobarography using Optimization Techniques, Electronic Letters on Computer Vision and Image Analysis 5(3):

47 Structures Matching Example: matching contours with order restriction (geometrical modeling, optimization, dynamic programming) Original images and contours Matching found without order restriction Matching found with order restriction Bastos & Tavares (2006), Matching of Objects Nodal Points Improvement using Optimization, Inverse Problems in Science and Engineering 14(5): Oliveira & Tavares (2008), Algorithm of dynamic programming for optimization of the global matching between two contours defined by ordered points, Computer Modeling in Engineering & Sciences 31(1):

48 Structures Morphing Example: morphing contours (FEM, Modal Analysis, optimization) Original images Contours matched Estimated deformations Matching found Estimated deformations Tavares & Pinho (2005), Estimação Temporal da Deformação entre Objectos utilizando uma Metodologia Física, InfoComp 4(1):9-18 Gonçalves et al. (2008), Segmentation and Simulation of Objects Represented in Images using Physical Principles, Computer Modeling in Engineering & Sciences 32(1):

49 Structures Morphing Example: morphing contours (FEM, Modal Analysis, optimization) Original images Matching found Deformations estimated Gonçalves et al. (2008), Segmentation and Simulation of Objects Represented in Images using Physical Principles, Computer Modeling in Engineering & Sciences 32(1):

50 Structures Registration Example: registration of contours in images (geometrical modeling, optimization, dynamic programming) Original images and contours found Matched contours before registration Matched contours after registration Oliveira & Tavares (in press), Matching Contours in Images using Curvature and Distance to Centroid Information and Dynamic Programming, Computer Modeling in Engineering & Sciences 50

51 Structures Registration Example: registration of images in dynamic pedobarography (geometrical modeling, optimization, dynamic programming) Original images and contours found Contours and images before registration Contours and images after registration 51

52 Structures Registration Example: registration of images in dynamic pedobarography (geometrical modeling, optimization, dynamic programming) Original images and contours found Contours matched before registration Images after registration 52

53 Structures Registration Example: registration of brain images in the diagnosis of multiple sclerosis lesions After rotation Source image Target image After translation After scale Jacob et al. (2009), Algoritmos para Alinhamento de Imagens Médicas: Princípios e Aplicação em Imagens de Esclerose Múltipla, 3º Congresso Nacional de Biomecânica, Portugal,

54 Tasks and Applications: Structures 3D Reconstruction

55 Structures 3D Reconstruction It is intended to accomplish the 3D reconstruction of structures from images In this area, the following methodologies are common: external shapes active techniques (with energy projection or relative movement), passive techniques (without energy projection or relative movement) and of space carving; interior shapes 2D segmentation (contours, for example) and interpolation Usually, it involves tasks of camera calibration, data segmentation, matching, triangulation and interpolation Common problems: geometric distortion, bad or varying illumination conditions, occlusion, noise, multiple structures, complex shapes, etc. 55

56 Structures 3D Reconstruction Example: 3D reconstruction of organs from medical images Segmentation done in a slice and 3D reconstruction obtained Perdigão et al. (2005), Sobre a Geração de Malhas Tridimensionais para fins Computacionais a partir de Imagens Médicas, CMNI 2005, España 3D reconstruction of some structures of the arm João Manuel R. S. Tavares Análise de Estruturas em Imagens: Segmentação, Seguimento e Reconstrução 3D 56

57 Structures 3D Reconstruction Example: 3D reconstruction of organs from medical images slices Segmentation done in a slice Pelvic floor reconstructed Reconstructed structures of the pelvic cavity Pimenta et al. (2006), Reconstruction of 3D Models from Medical Images: Application to Female Pelvic Organs, CompIMAGE 2006, Coimbra, Portugal, Alexandre et al. (2007), 3D reconstruction of pelvic floor for numerical simulation purpose, VipIMAGE 2007, Porto, Portugal,

58 Structures 3D Reconstruction Example: 3D reconstruction using techniques of active vision Original image pair Disparity map obtained Azevedo et al. (2006), Development of a Computer Platform for Object 3D Reconstruction using Active Vision Techniques, VISAPP 2006, Portugal,

59 Structures 3D Reconstruction Example: 3D reconstruction using space carving Original images Computational 3D model built: voxelized and poligonized Azevedo et al. (2008), 3D Object Reconstruction from Uncalibrated Images using an Off-the- Shelf Camera, Advances in Computational Vision and Medical Image Processing: Methods and Applications,

60 Structures 3D Reconstruction Example: 3D reconstruction using space carving Original images Computational 3D model built: voxelized and poligonized Azevedo et al. (2008), 3D Object Reconstruction from Uncalibrated Images using an Off-the- Shelf Camera, Advances in Computational Vision and Medical Image Processing: Methods and Applications,

61 Human Perception and Data Visualization

62 Human Perception and Data Visualization Recently, some projects involving the visualization and analysis of complex, large and crucial data have been developed based on principles of human perception visualization and analysis of huge volumes of data visualization and analysis of temporal critical data 62

63 Human Perception and Data Visualization Example: visualization and analysis of huge volumes of computational data Computational interface developed to visualize and analyze the data of a composite bolted joint simulator Gonçalves & Tavares (2008), A GUI for a Software that Analyses a Composite Bolted Joint, e-minds: International Journal on Human-Computer Interaction I(4):

64 Human Perception and Data Visualization Example: visualization and analysis of critical data in air traffic control (ATC) Computational interface developed to analyze and evaluate the use of visualization filters based on human perception in tasks of visual searching in ATC displays Sousa & Tavares (submitted), ATCBlur: an Air Traffic Control display filtering tool, International Journal of Human-Computer Studies 64

65 Research Projects & PhD Thesis

66 Research Projects & PhD Thesis In the last years, we have been involved in some national and international research projects, as research team members as well as project coordinators Currently, we have several PhD thesis undergoing considering important topics of image processing and analysis See: 66

67 Research Projects & PhD Thesis Research Projects (in course) Biomechanical study of the middle ear for auditory rehabilitation Coordinator: Renato M. Natal Jorge, FEUP Institution: IDMEC - Polo FEUP Financing Institution: FCT, ,00 Duration: 36 months, started in July 2007 BIOPELVIC - Study of Female Pelvic Floor Disorders Coordinator: Renato M. Natal Jorge, FEUP Institutions: IDMEC - Polo FEUP, FMUP, INESC-Porto Financing Institution: FCT, ,00 Duration: 36 months, started in July 2007 See: 67

68 Research Projects & PhD Thesis Research Projects (in course) Rede Luso-Brasileiro de Bioengenharia Coordinator: Renato M. Natal Jorge, FEUP Financing Institution: GRICES/CAPES 2007 Duration: 36 months, started in January 2007 Aberrant Crypt Foci and Human Colorectal Polyps: mathematical modelling and endoscopic image processing Coordinator: Isabel Figueiredo, FCT/UC-PT Institutions: FCT/UC-PT, FEUP-PT, FM/UC-PT, IT-PT, UTA-USA Financing Program: UT Austin Portugal 2008 Duration: 48 months, started in April 2009 (?) See: 68

69 Research Projects & PhD Thesis Research Projects (in course) Cardiovascular Imaging Modeling and Simulation - SIMCARD Coordinator: Adélia Sequeira, IST-PT Institutions: IST-PT, FEUP-PT, HSM-PT, SPRM-PT, UTA-USA Financing Program: UT Austin Portugal 2008 Duration: 24 months, started in April 2009 (?) See: 69

70 Research Projects & PhD Thesis Research Projects (finished) BioSpine Development of External Biocompatible Prosthesis/Vests Coordinator: Manuel Laranjeira Gomes, ICBAS Institutions: INEGI, INEB, ICBAS Financing Institution: ADI, ,00 Duration: 24 months, started in January 2007 ACTIDEF Integrated Computational and Technological Evaluation of the Performance and Functionality of Citizens with Muscular Incapacities Coordinator: Jerónimo de Sousa, CRPG Institutions: CRPG, INEB, INEGI Financing Program: POS_C, ,00 Duration: 12 months, started in February 2006 See: 70

71 Research Projects & PhD Thesis Research Projects (finished) Segmentation, Tracking and Motion Analysis of Deformable (2D/3D) Objects using Physical Principles Coordinator: João Manuel R. S. Tavares Participant Institutions: INEGI, INEB Financing Institution: FCT, ,00 Duration: 36 months, started in May 2005 See: 71

72 Research Projects & PhD Thesis PhD Thesis (in course) Analysis of Movement using Computational Vision Student: Raquel R. Pinho Supervisor: João Manuel R. S. Tavares Co-supervisor: Miguel V. Correia, FEUP PhD in Engineering Sciences, University of Porto, since April 2003 Application of Physical Principles in the Analysis of Objects Represented in Images Student: Patrícia C. T. Gonçalves Supervisor: João Manuel R. S. Tavares Co-supervisor: R. M. Natal Jorge, FEUP PhD in Engineering Sciences, University of Porto, since February 2006 See: 72

73 Research Projects & PhD Thesis PhD Thesis (in course) Computational Modeling for the Analysis of the Mechanical Behavior of Structures represented in Image Sequences: Applications in Medical Images Student: Ilda M. de Sá Reis Supervisor: João Manuel R. S. Tavares Co-supervisors: R. M. Natal Jorge, FEUP, A. F. Leite-Moreira, FMUP PhD in Engineering Sciences, University of Porto, since March 2007 Unsupervised Geometrical Modelling of the Scoliotic Spine from Radiographs Student: Daniel C. de Moura Supervisor: Jorge G. Barbosa, FEUP Co-supervisor: João Manuel R. S. Tavares Doctoral Program in Informatics, University of Porto, since September 2006 See: 73

74 Research Projects & PhD Thesis PhD Thesis (in course) Modeling the Shape and Motion of Objects in Image Sequences: Applications in Biomechanics of the Human Body Student: Maria J. M. de Vasconcelos Supervisor: João Manuel R. S. Tavares Co-supervisor: Miguel V. Correia, FEUP PhD in Engineering Sciences, University of Porto, since July 2007 Reconstruction of 3D Objects Shape using Computational Vision: Applications in the Reconstruction and Characterization of External Anatomical Structures Student: Teresa C. S. Azevedo Supervisor: João Manuel R. S. Tavares Co-supervisor: Mário A. P. Vaz, FEUP PhD in Engineering Sciences, University of Porto, since October 2006 See: 74

75 Research Projects & PhD Thesis PhD Thesis (in course) Computational Methodologies for Three-Dimensional Reconstruction and Recognition of Shape and Motion Patterns in the Analysis of Dynamic Fluid Flow in Automotive Conditional Air Systems Student: Elza M. P. F. Chagas Supervisor: Denilson L. Rodrigues, PCU-MG Brazil Co-supervisor: João Manuel R. S. Tavares PhD Thesis in Mechanical Engineering, PCU-MG Brazil, since January 2007 See: 75

76 Research Projects & PhD Thesis PhD Thesis (in course) Image Processing and Analysis in the Characterization of Parts and Operations Student: Victor H. C. de Albuquerque Supervisor: João Manuel R. S. Tavares Co-supervisor: Luís M. P. Durão, ISEP PhD in Engineering Sciences, University of Porto, since July 2007 Segmentation, Tracking and 3D Reconstruction of Structures Represented in Images: Applications in Medical Images Student: Zhen Ma Supervisor: João Manuel R. S. Tavares Co-supervisor: R. M. Natal Jorge, FEUP PhD in Engineering Sciences, University of Porto, since July 2007 See: 76

77 Research Projects & PhD Thesis PhD Thesis (in course) Matching and Registration of Structures in Computational Vision: Applications in Medical Images Student: Francisco P. M. de Oliveira Supervisor: João Manuel R. S. Tavares Co-supervisor: Durval C. Costa, HPP-Medicina Molecular, SA. Doctoral Program in Biomedical Engineering, University of Porto, since 2008/2009 Neuronal Quantitative Evaluation in Tensor Diffusion Images Student: Eduardo F. C. Ribeiro Supervisor: João Manuel R. S. Tavares Co-supervisors: A. M. Reis, PHH, Chandrajit Bajaj, UTA Doctoral Program in Biomedical Engineering, University of Porto, since 2008/2009 See: 77

78 Research Projects & PhD Thesis PhD Thesis (in course) Methodologies and Active Systems based on Sensorial Fusion for Movement Analysis Applications in Biomechanics Student: António F. N. Gomes Supervisor: João Manuel R. S. Tavares Co-supervisor: Joaquim G. Mendes, FEUP Doctoral Program in Mechanical Engineering, University of Porto, since 2008/2009 See: 78

79 Scientific Events & Publications

80 Scientific Events & Publications In the last years, we have been involved in the organization of several scientific events mini-symposia, workshops and conferences and in the editing of several scientific publications conferences proceedings books, special issue of journals and the editing of scientific journals See: 80

81 Events & Publications Conferences, Symposia and Workshops Co-chair: National Meeting on Scientific Visualization Portugal, 17 September 2005 Co-chair: CompIMAGE - Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications Portugal, October 2006 See: 81

82 Events & Publications Conferences, Symposia and Workshops Thematic session Image processing, Visualization and Interfaces Métodos Numéricos em Engenharia (CMNE) & XXVIII CILAMCE - Congresso Ibero Latino-Americano sobre Métodos Computacionais em Engenharia Portugal, June 2007 Co-chair: VIPimage I ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing Portugal, October 2007 See: 82

83 Events & Publications Conferences, Symposia and Workshops Mini-Symposium Computational Methods in Image Analysis The ninth U.S. National Congress on Computational Mechanics (USNCCM IX) USA, July 2007 Mini-symposium Computational Bioimaging and Visualization VIII World Conference on Computational Mechanics (WCCM VIII) & V European Congress on Computational Methods in Applied Science and Engineering (ECCOMAS V) Italy, 30 June - 5 July 2008 See: 83

84 Events & Publications Conferences, Symposia and Workshops Co-chair: Workshop: Applications of a Movement Analysis Lab Portugal, 23 March 2007 Mini-Symposium Image Processing and Analysis ICCES08 - International Conference on Computational and Experimental Engineering & Sciences Hawaii, March 2008 See: 84

85 Events & Publications Conferences, Symposia and Workshops Mini-Symposium Image Processing and Visualization 5º Congresso Luso-Moçambicano de Engenharia Mozambique, 2-4 September 2008 Workshop Medical Imaging Systems EUROMEDIA The Multimedia Applications Conference Portugal, 9-11 April 2008 See: 85

86 Events & Publications Conferences, Symposia and Workshops Co-chair: EUROMEDIA The Multimedia Applications Conference Portugal, 9-11 April 2008 International Workshop on Combinatorial Image Analysis (IWCIA'08) USA, 7-9 April 2008 See: 86

87 Events & Publications Conferences, Symposia and Workshops Mini-Symposium Biomechanical Behavior of Soft Tissues Mini-Symposium Computational Methods in Image Processing for Biomechanics CMBBE2008-8th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering Portugal, 27 February - 1 March 2008 Special Track Computational Bioimaging and Visualization ISVC08-4th International Symposium on Visual Computing USA, 1-3 December 2008 See: 87

88 Events & Publications Conferences, Symposia and Workshops Co-chair: 1st International Conference on Imaging Theory and Applications (IMAGAPP) Portugal, 5-8 February 2009 Mini-Symposium Image Processing and Analysis ICCES'09 - Int. Conference on Computational and Experimental Engineering & Sciences Thailand, 8-13 April 2009 See: 88

89 Events & Publications Conferences, Symposia and Workshops Mini-Symposium Image Processing and Data Visualization SEECCM nd South-East European Conference on Computational Mechanics Greece, June 2009 Thematic Session Image Processing, Visualization and Interfaces Congreso de Métodos Numéricos en Ingeniería 2009 Spain, 29 June - 2 July 2009 See: 89

90 Events & Publications Conferences, Symposia and Workshops Mini-Symposium Computational Methods in Image Analysis 10th US National Congress of Computational Mechanics USA, July 2009 Mini-Symposium Image Processing and Visualization in Solid Mechanics Processes 7th EUROMECH Solid Mechanics Conference ESMC2009 Portugal, 7-11 September 2009 See: 90

91 Events & Publications Conferences, Symposia and Workshops Workshop Medical Imaging Systems EUROMEDIA The Multimedia Applications Conference Belgium, April 2009 Mini-Symposium Visualization and Human-Computer Interaction IRF 2009 Integrity - Reliability - Failure Challenges and Opportunities Portugal, July 2009 See: 91

92 Events & Publications Conferences, Symposia and Workshops Co-chair: I International Conference on Biodental Enginnering Portugal, June 2009 Co-chair: 6th International Conference on Technology and Medical Sciences Portugal, October 2010 See: 92

93 Events & Publications Conferences, Symposia and Workshops Co-chair: VIPimage II ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing Portugal, October 2009 Submissions are Opened Co-chair: CompIMAGE'2010 Symposium - Computational Modeling of Objects Represented in Images: Fundamentals, Methods and Applications USA, 5-7 May 2010 See: 93

94 Events & Publications Books, Journals and special issues Co-editor: Proceedings of the ENVC2005 National Meeting on Scientific Visualization ISBN: , Fundação Navegar, 2005 Co-editor-in-chief: Int. Journal for Computational Vision and Biomechanics (IJCV&B) ISSN: , Serials Publications Co-editor: Proceedings of the International Symposium CompIMAGE 2006 ISBN: , Taylor and Francis, 2007 See: 94

95 Events & Publications Books, Journals and special issues Guest-co-editor: Special issue of the International Journal of Simulation Modelling (IJSM) dedicated to CompIMAGE 2006 ISSN , Vol. 6, N. 2, June 2007, pp Guest-co-editor: Special issue of Electronic Letters on Computer Vision and Image Analysis (ELCVIA) dedicated to CompIMAGE 2006 ISSN , Vol. 7, N. 2, May 2008 See: 95

96 Events & Publications Books, Journals and special issues Co-editor: Proceedings of the I ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing: VipIMAGE 2007 ISBN: , Taylor and Francis, 2007 Co-editor: Advances in Computational Vision and Medical Image Processing: Methods and Applications Computational Methods in Applied Sciences, Vol. 13 ISBN: , Springer, 2008 See: 96

97 Events & Publications Books, Journals and special issues Guest-co-editor: Special issue of the International Journal of Tomography & Statistics on Image Processing ISSN: , Vol. 15, N. W10, Winter 2010 & Vol. 16, N. S10, Summer 2010 Co-editor: Fourteenth Annual Scientific Conference on web Technology, New Media, Communications and Telematics Theory and Applications ISBN: , EUROSIS-ETI, 2008 See: 97

98 Events & Publications Books, Journals and special issues Guest-co-editor: Special issue of the EURASIP Journal on Advances in Signal Processing on Image Processing and Analysis in Biomechanics ISSN: , Hindawi Publishing Corporation Submission is Opened Co-editor: Proceedings of the 1st International Conference on Imaging Theory and Applications (IMAGAPP) ISSN: , INSTICC Press, 2009 See: 98

99 Research Team (Computational Vision)

100 Research Team (Computational Vision) PhD students (12): In course: Raquel Pinho, Patrícia Gonçalves, Maria Vasconcelos, Ilda Reis, Teresa Azevedo, Daniel Moura, Zhen Ma, Elza Chagas, Victor Albuquerque, Francisco Oliveira, Eduardo Ribeiro, Eduardo Gomes MSc students (13): In course: Fernando Carvalho, Mauro Trindade, Lara Quintela, Frederico Jacob, Verónica Marques Finished: Daniela Sousa, Francisco Oliveira, Teresa Azevedo, Maria Vasconcelos, Raquel Pinho, Luísa Bastos, Cândida Coelho, Jorge Gonçalves BSc students (2) Finished: Ricardo Ferreira, Soraia Pimenta 100

101 Research Team (Computational Vision) Collaborators: Renato Natal Jorge, Joaquim Gabriel, Mário Vaz, Miguel Velhote, Jorge Barbosa, Francisco Freitas (FEUP) Nuno Correia (INEGI) Luís Durão (ISEP) Emília Mendes (CRPG) Denilson Rodrigues (PUC - Minas Gerais, Brazil) Diana Miranda, Georgeta Oliveira, Ricardo Duarte (HPH) Ana Mafalda Reis, Manuel Laranjeira (ICBAS/INC) Manuel Paulo (FMDUP) Adelino Leite-Moreira (FMUP) Filipa Sousa, João Paulo Vilas-Boas (FCDUP) 101

102 Research Team (Computational Vision) Collaborators: Durval C. Costa (HPP-Medicina Molecular, SA.) Luis Metello (ESTSP) Chandrajit Bajaj (UTA, USA) Todd Pataky (University of Liverpool, UK) Chris Constantinou (Stanford University of Medicine, USA) Isabel Figueiredo (FCT/UC) Adélia Cerqueira (IST) 102

103 Conclusions and Future Working Perspectives

104 Conclusions and Future Working Perspectives The computer analysis of structures in images is a very complex task, but of raised importance in many domains Numerous complex challenges exist, as for example, structures with topological variations, complex movements, adverse conditions in the image acquisition processes, etc. Much work was already developed in this Computational Vision area, but important and complex goals still to be successfully addressed Methods and methodologies of other research areas, as of Mathematics, Computational Mechanics and Biology, can contribute significantly for its development For that, collaborations are mostly welcome 104

105 A computer analysis of structures in image sequences: methods and applications João Manuel R. S. Tavares Mathematical Aspects of Imaging, Modeling and Visualization in Multiscale Biology March 31 April 4, 2009, The University of Texas at Austin, USA