Image Analysis and Tomography

Image analysis is the use of computers to extract quantitative information from images, such as those that arise from microscopes, medical scanners, electrophoresis gels, and illuminated objects. We give examples of such images, an overview of the different types of digital image, and the eclectic collection of methodologies that have been proposed to analyse them. We then consider the tomographic reconstruction of images from projections, and the three major components of image analysis: enhancement, segmentation, and taking measurements. We illustrate the methods using the examples. Keywords: Bayesian image analysis; deconvolution; image warping; mathematical morphology; pattern recognition; segmentation; signal processing stereology

[1]  C. A. Glasbey,et al.  Towards the Automatic Measurement of Cashmere-fibre Diameter by Image Analysis , 1994 .

[2]  D. Burr.  A dynamic model for image registration , 1981 .

[3]  B. Silverman,et al.  Nonparametric regression and generalized linear models , 1994 .

[4]  Theodosios Pavlidis,et al.  A review of algorithms for shape analysis , 1978 .

[5]  B F Hutton,et al.  Use of 3D reconstruction to correct for patient motion in SPECT. , 1994, Physics in medicine and biology.

[6]  Richard M. Leahy,et al.  Statistic-based MAP image-reconstruction from Poisson data using Gibbs priors , 1992, IEEE Trans. Signal Process..

[7]  D. Stoyan.  Stereology and stochastic geometry , 1990 .

[8]  P. Green,et al.  Modelling data from single photon emission computed tomography , 1994 .

[9]  T. V. Price,et al.  Computer imaging and its application to some problems in agriculture and plant science , 1990 .

[10]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  L. Shepp,et al.  Maximum Likelihood Reconstruction for Emission Tomography , 1983, IEEE Transactions on Medical Imaging.

[12]  C A Glasbey,et al.  An algorithm for unwarping multitrack electrophoretic gels , 1994, Electrophoresis.

[13]  Edmond J. Breen,et al.  An Evaluation of Priority Queues for Mathematical Morphology , 1994, ISMM.

[14]  F. Rohlf,et al.  A COMPARISON OF FOURIER METHODS FOR THE DESCRIPTION OF WING SHAPE IN MOSQUITOES (DIPTERA: CULICIDAE) , 1984 .

[15]  D. M. Titterington,et al.  A Study of Methods of Choosing the Smoothing Parameter in Image Restoration by Regularization , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  N. Cressie,et al.  A statistical approach to identifying closed object boundaries in images , 1994, Advances in Applied Probability.

[17]  D. M. Titterington,et al.  Pixel labelling for three-dimensional scenes based on Markov mesh models , 1991, Signal Process..

[18]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[19]  J. Kay.  Statistical models for PET and SPECT data , 1994, Statistical methods in medical research.

[20]  A. D. Gordon.  A survey of constrained classification , 1996 .

[21]  Michael I. Miller,et al.  The Use of Sieves to Stabilize Images Produced with the EM Algorithm for Emission Tomography , 1985, IEEE Transactions on Nuclear Science.

[22]  Tomaso Poggio,et al.  Probabilistic Solution of Ill-Posed Problems in Computational Vision , 1987 .

[23]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[25]  Alberto Martelli,et al.  An application of heuristic search methods to edge and contour detection , 1976, CACM.

[26]  Max A. Viergever,et al.  Evaluation of Fully 3D Iterative Scatter Compensation and Post-Reconstruction Filtering In SPECT , 1996 .

[27]  J H McColl,et al.  Statistical methods in neuroimaging with particular application to emission tomography , 1994, Statistical methods in medical research.

[28]  Daiqing Mou,et al.  SEPARATING TABELLARIA (BACILLARIOPHYCEAE) SHAPE GROUPS BASED ON FOURIER DESCRIPTORS 1 , 1992 .

[29]  F. O’Sullivan,et al.  Metabolic images from dynamic positron emission tomography studies , 1994, Statistical methods in medical research.

[30]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  N. A. Campbell,et al.  ALLOCATION OF REMOTELY SENSED DATA USING MARKOV MODELS FOR IMAGE DATA AND PIXEL LABELS , 1992 .

[32]  Carlos Pomalaza-Raez,et al.  Comparison Study Of Nonlinear Filters In Image Processing Applications , 1989 .

[33]  B. Ardekani,et al.  CHAPTER 23 – Minimum Cross-Entropy Reconstruction of PET Images Using Prior Anatomical Information Obtained from MR , 1996 .

[34]  Donald Geman,et al.  Boundary Detection by Constrained Optimization , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[36]  R. Bajcsy,et al.  Elastically Deforming 3D Atlas to Match Anatomical Brain Images , 1993, Journal of computer assisted tomography.

[37]  Yuan Yan Tang,et al.  Image transformation approach to nonlinear shape restoration , 1993, IEEE Trans. Syst. Man Cybern..

[38]  Ralph Roskies,et al.  Fourier Descriptors for Plane Closed Curves , 1972, IEEE Transactions on Computers.

[39]  Russell M. Mersereau,et al.  Blur identification by the method of generalized cross-validation , 1992, IEEE Trans. Image Process..

[40]  Alfred M. Bruckstein,et al.  Design of Perimeter Estimators for Digitized Planar Shapes , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Peter J. Bickel,et al.  Estimating linear functionals of a PET image , 1995, IEEE Trans. Medical Imaging.

[42]  H. Malcolm Hudson,et al.  Accelerated image reconstruction using ordered subsets of projection data , 1994, IEEE Trans. Medical Imaging.

[43]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[44]  P. Green.  Bayesian reconstructions from emission tomography data using a modified EM algorithm. , 1990, IEEE transactions on medical imaging.

[45]  Brian F. Hutton,et al.  A clinical perspective of accelerated statistical reconstruction , 1997, European Journal of Nuclear Medicine.

[46]  A. L. Sutherland,et al.  Finding spiral structures in images of galaxies , 1990, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.

[47]  Ruzena Bajcsy,et al.  Multiresolution elastic matching , 1989, Comput. Vis. Graph. Image Process..

[48]  P. Green,et al.  Global and local priors, and the location of lesions using gamma-camera imagery , 1991, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.

[49]  C. Glasbey,et al.  Uses of digital image analysis in electrophoresis , 1995, Electrophoresis.

[50]  F. O’Sullivan,et al.  Bandwidth Selection for Indirect Density Estimation Based on Corrupted Histogram Data , 1996 .

[51]  D. Girard.  Optimal Regularized Reconstruction in Computerized Tomography , 1987 .

[52]  Knut Conradsen,et al.  Analysis of Two-Dimensional Electrophoretic Gels , 1992 .

[53]  Pierre A. Devijver,et al.  Learning the parameters of a hidden Markov random field image model: A simple example , 1987 .

[54]  Manfred H. Hueckel.  An Operator Which Locates Edges in Digitized Pictures , 1971, J. ACM.

[55]  T. Jones,et al.  Spectral Analysis of Dynamic PET Studies , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[56]  J. Skilling,et al.  Maximum entropy image reconstruction: general algorithm , 1984 .

[57]  D. Jeulin.  Random models for morphological analysis of powders , 1993 .

[58]  Adrian F. M. Smith,et al.  Bayesian Faces via Hierarchical Template Modeling , 1994 .

[59]  Brian Fenton,et al.  Superimposing two‐dimensional gels to study genetic variation in malaria parasites , 1992, Electrophoresis.