Recursive filtering of images with symmetric extension

Recursive filters are widely used in image analysis due to their efficiency and simple implementation. However these filters have an initialisation problem which either produces unusable results near the image boundaries or requires costly approximate solutions such as extending the boundary manually. In this paper, we describe a method for the recursive filtering of symmetrically extended images for filters with symmetric denominator. We begin with an analysis of symmetric extensions and their effect on non-recursive filtering operators. Based on the non-recursive case, we derive a formulation of recursive filtering on symmetric domains as a linear but spatially varying implicit operator. We then give an efficient method for decomposing and solving the linear implicit system, along with a proof that this decomposition always exists. This decomposition needs to be performed only once for each dimension of the image. This yields a filtering which is both stable and consistent with the ideal infinite extension. The filter is efficient, requiring less computation than the standard recursive filtering. We give experimental evidence to verify these claims. (c) 2005 Elsevier B.V. All rights reserved.

An analysis of the images attached to referral messages in an e-mail based telemedicine system for developing countries

Little is known about the quality of the images transmitted in email telemedicine systems. The present study was designed to survey the quality of images transmitted in the Swinfen Charitable Trust email referral system. Telemedicine cases were examined for a 3 month period in 2002 and a 3 month period in 2006. The number of cases with images attached increased from 8 (38%) to 37 (53%). There were four types of images (clinical photographs, microscope pictures, notes and X-ray images) and the proportion of radiology images increased from 27 to 48%. The cases in 2002 came from four different hospitals and were associated with seven different clinical specialties. In 2006, the cases came from 19 different hospitals and 20 different specialties. The 46 cases (from both study periods) had a total of 159 attached images. The quality of the images was assessed by awarding each image a score in four categories: focus, anatomical perspective, composition and lighting. The images were scored on a five-point scale (1 = very poor to 5 =very good) by a qualified medical photographer. In comparing image quality between the two study periods, there was some evidence that the quality had reduced, although the average size of the attached images had increased. The median score for all images in 2002 was 16 (interquartile range 14-19) and the median score in 2006 was 15 (13-16). The difference was significant (P < 0.001, Mann-Whitney test).

Genetic algorithm optimization of adaptive multi-scale GLCM features

We introduce a new second-order method of texture analysis called Adaptive Multi-Scale Grey Level Co-occurrence Matrix (AMSGLCM), based on the well-known Grey Level Co-occurrence Matrix (GLCM) method. The method deviates significantly from GLCM in that features are extracted, not via a fixed 2D weighting function of co-occurrence matrix elements, but by a variable summation of matrix elements in 3D localized neighborhoods. We subsequently present a new methodology for extracting optimized, highly discriminant features from these localized areas using adaptive Gaussian weighting functions. Genetic Algorithm (GA) optimization is used to produce a set of features whose classification worth is evaluated by discriminatory power and feature correlation considerations. We critically appraised the performance of our method and GLCM in pairwise classification of images from visually similar texture classes, captured from Markov Random Field (MRF) synthesized, natural, and biological origins. In these cross-validated classification trials, our method demonstrated significant benefits over GLCM, including increased feature discriminatory power, automatic feature adaptability, and significantly improved classification performance.

An e-health needs assessment of medical residents in Cameroon

Medical residents from Yaounde I University in Cameroon are required to spend periods of time in rural or remote locations to complete their training. To determine if e-health might lessen their isolation and enhance patient care, a needs assessment of the residents was performed using a brief questionnaire (five items) about the situation in which residents found themselves outside their medical school environment. We gave the questionnaires to 45 residents. Seventeen questionnaires had been returned at the time of the site visit, a response rate of 38%. Most residents indicated that the ability to contact a mentor would have either made them feel more confident (16, or 94%) or altered their handling of recent cases (15, or 88%). All residents had access to a mobile phone, and many (11, or 65%) had used it to contact a medical colleague for guidance. A low-cost and technologically simple telemedicine solution that maximized use of mobile phone capability, provided access to medical and health-care information, and permitted exchange of images would be an appropriate response to the identified needs.

Numerical modeling of 11.1 T MRI of a human head using MoM/FDTD methods

In a recent study, severe distortions in the proton images of an excised, fixed, human brain in an 11.1 Tesla/40 cm MR instrument have been observed, and the effect modeled on phantom images using a finite difference time domain (FDTD) model. in the present study, we extend these simulations to that of a complete human head, employing a hybrid FDTD and method of moments (MoM) approach, which provides a validated method for simulating biological samples in coil structures. The effect of fixative on the image distortions is explored. importantly, temperature distributions within the head are also simulated using a bioheat method based on parameters derived from the electromagnetic simulations. The MoM/FDTD simulations confirm that the transverse magnetic field (B,) from a ReCav resonator exhibits good homogeneity in air but strong inhomogeneity when loaded with the head with or without fixative. The fixative serves to increase the distortions, but they are still significant for the in vivo simulations. The simulated signal intensity (SI) distribution within the sample confirm the distortions in the experimental images are caused by the complex interactions of the incident electromagnetic fields with tissue, which is heterogeneous in terms of conductivity and permittivity. The temperature distribution is likewise heterogeneous, raising concerns regarding hot spot generation in the sample that may exceed acceptable levels in future in vivo studies. As human imaging at 11.1 T is some time away, simulations are important in terms of predicting potential safety issues as well as evaluating practical concerns about the quality of images. Simulation on a whole human head at 11.1 T implies the wave behavior presents significant engineering challenges for ultra-high-field (UHF) MRI. Novel strategies will have to be employed in imaging technique and resonator design for UHF MRI to achieve the theoretical signal-to-noise ratio (SNR) improvements it offers over lower field systems. (C) 2005 Wiley Periodicals, Inc.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.

A neural network based technique for automatic classification of road cracks

This paper presents a neural network based technique for the classification of segments of road images into cracks and normal images. The density and histogram features are extracted. The features are passed to a neural network for the classification of images into images with and without cracks. Once images are classified into cracks and non-cracks, they are passed to another neural network for the classification of a crack type after segmentation. Some experiments were conducted and promising results were obtained. The selected results and a comparative analysis are included in this paper.

Fetal endoscopic telesurgery using an Internet protocol connection: clinical and technical challenges

Until recently, fetoscopic laser surgery to seal the placental anastomoses that cause severe twin-to-twin transfusion syndrome has been available in only a few centres worldwide. The technique typically takes a long time to learn. We have used a dedicated Internet Protocol (IP) connection for tele-education to assist the introduction of fetoscopic laser surgery to Australia. During the implementation of the international telemedicine link, there were multiple clinical and technical problems, which were eventually overcome. The quality of images and of video-sequences was comparable to that supported by an ISDN connection. Pictures of live surgery performed by an expert in Florida, USA, were transmitted and viewed by a novice team in Brisbane, Australia. The Australian team has performed 19 fetoscopic laser operations to date. Preliminary results are comparable to those from centres that have performed over 100 procedures.

Beauty and the market: Actress postcards and their senders in early twentieth century Australia

A hundred years ago the international craze for picture postcards distributed millions of images of popular stage actresses around the world. The cards were bought, sent, and collected by many whose contact with live theatre was sometimes minimal. Veronica Kelly's study of some of these cards sent in Australia indicates the increasing reach of theatrical images and celebrity brought about by the distribution mechanisms of industrial mass modernity. The specific social purposes and contexts of the senders are revealed by cross-reading the images themselves with the private messages on the backs, suggesting that, once outside the industrial framing of theatre or the dramatic one of specific roles, the actress operated as a multiply signifying icon within mass culture – with the desires and consumer power of women major factors in the consumption of the glamour actress card. A study of the typical visual rhetoric of these postcards indicates the authorized modes of femininity being constructed by the major postcard publishers whose products were distributed to theatre fans and non-theatregoers alike through the post. Veronica Kelly is working on a project dealing with commercial managements and stars in early twentieth-century Australian theatre. She teaches in the School of English, Media Studies, and Art History at the University of Queensland, is co-editor of Australasian Drama Studies, and author of databases and articles dealing with colonial and contemporary Australian theatre history and dramatic criticism. Her books include The Theatre of Louis Nowra (1998) and the collection Our Australian Theatre in the 1990s (1998).

Using the Amazon metric to construct an image database based on what people do, not what they say

Current image database metadata schemas require users to adopt a specific text-based vocabulary. Text-based metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat's semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amazon.com returns other products also, based on an averaging of how users navigate the database. In this paper, we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation, searching, and browsing facilities.