Vladimir Petrovic

Bio: Vladimir Petrovic is an academic researcher from University of Novi Sad. The author has contributed to research in topics: Image fusion & Medicine. The author has an hindex of 20, co-authored 99 publications receiving 3437 citations. Previous affiliations of Vladimir Petrovic include University of Manchester & Lancaster University.

Objective image fusion performance measure

Abstract: A measure for objectively assessing the pixel level fusion performance is defined. The proposed metric reflects the quality of visual information obtained from the fusion of input images and can be used to compare the performance of different image fusion algorithms. Experimental results clearly indicate that this metric is perceptually meaningful.

Gradient-based multiresolution image fusion

Abstract: A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

Analysis of Features for Rigid Structure Vehicle Type Recognition

Abstract: We describe an investigation into feature representations for rigid structure recognition framework for recognition of objects with a multitude of classes. The intended application is automatic recognition of vehicle type for secure access and traffic monitoring applications, a problem not hitherto considered at such a level of accuracy. We demonstrate that a relatively simple set of features extracted from sections of car front images can be used to obtain high performance verification and recognition of vehicle type (both car model and class). We describe the approach and resulting system in full, and the results of experiments comparing a wide variety of different features. The final system is capable of recognition rates of over 93% and verification equal error rates of fewer than 5.6% when tested on over 1000 images containing 77 different classes. The system is shown to be robust for a wide range of weather and lighting conditions.

Subjective tests for image fusion evaluation and objective metric validation

Abstract: This paper focuses on the methodology for perceptual image fusion assessment through comparative tests and validation of objective fusion evaluation metrics. Initially, the theory of subjective fusion evaluation, adopted practice and methods to gauge relevance and significance of individual trials are examined. Further in this context, the methodology, experiences and results of a series of specific, subjective preference tests aimed at relative evaluation of fusion algorithms are presented. Test conditions and experimental procedure are described in detail and a number of explicit fusion metrics derived from the subjective test data are proposed. Relative fusion quality, fusion performance robustness (to content) and personal preference are all assessed by the metrics as different aspects of general image fusion performance. Finally, the methodology for subjective validation of objective fusion metrics using the reported test procedures is presented. In particular, explicit subjective-objective validation algorithms are defined and applied to a range of established objective measures of fusion performance in order to evaluate their subjective relevance.

Objective pixel-level image fusion performance measure

Abstract: This paper addresses the issue of objectively measuring the performance of pixel level image fusion systems. The proposed fusion performance metric models the accuracy with which visual information is transferred from the input images to the fused image. Experimental results clearly indicate that the metric is perceptually meaningful.

Image Processing

Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

A Bayesian model of shape and appearance for subcortical brain segmentation

Abstract: Automatic segmentation of subcortical structures in human brain MR images is an important but difficult task due to poor and variable intensity contrast. Clear, well-defined intensity features are absent in many places along typical structure boundaries and so extra information is required to achieve successful segmentation. A method is proposed here that uses manually labelled image data to provide anatomical training information. It utilises the principles of the Active Shape and Appearance Models but places them within a Bayesian framework, allowing probabilistic relationships between shape and intensity to be fully exploited. The model is trained for 15 different subcortical structures using 336 manually-labelled T1-weighted MR images. Using the Bayesian approach, conditional probabilities can be calculated easily and efficiently, avoiding technical problems of ill-conditioned covariance matrices, even with weak priors, and eliminating the need for fitting extra empirical scaling parameters, as is required in standard Active Appearance Models. Furthermore, differences in boundary vertex locations provide a direct, purely local measure of geometric change in structure between groups that, unlike voxel-based morphometry, is not dependent on tissue classification methods or arbitrary smoothing. In this paper the fully-automated segmentation method is presented and assessed both quantitatively, using Leave-One-Out testing on the 336 training images, and qualitatively, using an independent clinical dataset involving Alzheimer's disease. Median Dice overlaps between 0.7 and 0.9 are obtained with this method, which is comparable or better than other automated methods. An implementation of this method, called FIRST, is currently distributed with the freely-available FSL package.

Gray's Anatomy

Abstract: MEDICAL LITERATURE has been deluged during the past few years with books and papers on penicillin; but a book which has been produced under the general editorship of Sir Alexander Fleming himself represents a complete and authoritative summary of penicillin therapy as it stands today.' The book contains a series of independent contributions by \"experienced and eminent men who have worked with penicillin in Great Britain\". Their opinions and practical methods differ slightly, and there is some overlapping; but these are not disadvantageous, comparison and contrast lending interest to the reading. In the first or general section of the book Fleming contributes two chapters, one on the history and development of penicillin, introducing some interesting sidelights in the romance of discovery, the other on the bacteriological control of penicillin therapy. In both chapters the information is set out in meticulous detail and with a clarity and simplicity which can be enjoyed by all readers. Fleming also gives the right perspective to the place of penicillin amongst the antibiotics and lays down the principles of treatment. Both chapters are well illustrated and are the most outstanding in the book. Included in this first section also are chapters on the chemistry and manufacture of penicillin and its pharmacy, pharmacology and methods of administration. The second section of the book is entirely clinical, giving each author's view on the use of penicillin therapy in a disease or an infection of some particular region of the body. The entire range of peniCillin-sensitive conditions is considered in twenty authoritative and clearly written chapters; these contain many references and illustrations. Dental and veterinary diseases are also given fairly full consideration. The final section is a condensed resume of much of the preceding chapters and is written for. the general practttioner. This chapter is superttuous: it does not contain enough detall to be of much practical value. The book as a Whole, however, will undoubtedly be considered a classical contribution to medical literature and is strongly recommended, not only because of the general interest of its topic, but as a reference book on penicillin therapy of hitherto unequalled excellence. The typography, although conforming to war economy standards, is clear and the paper is good. There is an excellent list of references and the index is satisfactory.

Objective image fusion performance measure

Abstract: A measure for objectively assessing the pixel level fusion performance is defined. The proposed metric reflects the quality of visual information obtained from the fusion of input images and can be used to compare the performance of different image fusion algorithms. Experimental results clearly indicate that this metric is perceptually meaningful.

Deformable Medical Image Registration: A Survey

Abstract: Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.