A pilot study on affective classification of facial images for emerging news topics

The proliferation of news reports published in online websites and news information sharing among social media users necessitates effective techniques for analysing the image, text and video data related to news topics. This paper presents the first study to classify affective facial images on emerging news topics. The proposed system dynamically monitors and selects the current hot (of great interest) news topics with strong affective interestingness using textual keywords in news articles and social media discussions. Images from the selected hot topics are extracted and classified into three categorized emotions, positive, neutral and negative, based on facial expressions of subjects in the images. Performance evaluations on two facial image datasets collected from real-world resources demonstrate the applicability and effectiveness of the proposed system in affective classification of facial images in news reports. Facial expression shows high consistency with the affective textual content in news reports for positive emotion, while only low correlation has been observed for neutral and negative. The system can be directly used for applications, such as assisting editors in choosing photos with a proper affective semantic for a certain topic during news report preparation.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Metal artifacts from titanium and steel screws in CT, 1.5T and 3T MR images of the tibial Pilon: A quantitative assessment in 3D

Radiographs are commonly used to assess articular reduction of the distal tibia (pilon) fractures postoperatively, but may reveal malreductions inaccurately. While Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are potential 3D alternatives they generate metal-related artifacts. This study aims to quantify the artifact size from orthopaedic screws using CT, 1.5T and 3T MRI data. Three screws were inserted into one intact human cadaver ankle specimen proximal to and along the distal articular surface, then CT, 1.5T and 3T MRI scanned. Four types of screws were investigated: titanium alloy (TA), stainless steel (SS) (Ø = 3.5 mm), cannulated TA (CTA) and cannulated SS (CSS)(Ø = 4.0 mm, Ø empty core = 2.6 mm). 3D artifact models were reconstructed using adaptive thresholding. The artifact size was measured by calculating the perpendicular distance from the central screw axis to the boundary of the artifact in four anatomical directions with respect to the distal tibia. The artifact sizes (in the order of TA, SS, CTA and CSS) from CT were 2.0 mm, 2.6 mm, 1.6 mm and 2.0 mm; from 1.5T MRI they were 3.7 mm, 10.9 mm, 2.9 mm, and 9 mm; and 3T MRI they were 4.4 mm, 15.3 mm, 3.8 mm, and 11.6 mm respectively. Therefore, CT can be used as long as the screws are at a safe distance of about 2 mm from the articular surface. MRI can be used if the screws are at least 3 mm away from the articular surface except SS and CSS. Artifacts from steel screws were too large thus obstructed the pilon from being visualised in MRI. Significant differences (P < 0.05) were found in the size of artifacts between all imaging modalities, screw types and material types, except 1.5T versus 3T MRI for the SS screws (P = 0.063). CTA screws near the joint surface can improve postoperative assessment in CT and MRI. MRI presents a favourable non-ionising alternative when using titanium hardware. Since these factors may influence the quality of postoperative assessment, potential improvements in operative techniques should be considered.

Datascape

"Contemporary society is in the midst of the boundless generation and collection of data, data that is produced from almost any measurable act. Be it weather or transport data sets published by government agencies, or the individual and interpersonal data generated by our digital interactions; a server somewhere is collating. With the rise of this digital data phenomenon comes questions of comprehension, purpose, ownership and translation. Without mediation digital data is an immense abstract list of text and numbers and in this abstracted form data sets become detached from the circumstances of their creation. Artists and digital creatives are building works from these constantly evolving data sets to develop a discourse that investigates, appropriates, reveals and reflects upon the society and environment that generates this medium. Datascape presents a range of works that use data as building blocks to facilitate connections and understanding around a range of personal, social and worldly issues. The exhibition is concerned with creating an opportunity for experiential discovery through engaging with work from some of the world’s prominent creatives in this field of practice. Utilising three thematic lenses: Generative Currents, the Anti-Sublime and the Human Context, the works offer a variety of pathways to traverse the Datascape. Lubi Thomas and Rachael Parsons, QUT Creative Industries Precinct"

An accuracy assessment of ASTER stereo images-derived digital elevation model by using rational polynomial coefficient model

The along-track stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor with 15 m resolution were used to generate Digital Elevation Model (DEM) on an area with low and near Mean Sea Level (MSL) elevation in Johor, Malaysia. The absolute DEM was generated by using the Rational Polynomial Coefficient (RPC) model which was run on ENVI 4.8 software. In order to generate the absolute DEM, 60 Ground Control Pointes (GCPs) with almost vertical accuracy less than 10 meter extracted from topographic map of the study area. The assessment was carried out on uncorrected and corrected DEM by utilizing dozens of Independent Check Points (ICPs). Consequently, the uncorrected DEM showed the RMSEz of ± 26.43 meter which was decreased to the RMSEz of ± 16.49 meter for the corrected DEM after post-processing. Overall, the corrected DEM of ASTER stereo images met the expectations.

Barbara's story : a thematic analysis of a relative's reflection of being in the intensive care unit

Aim The aim of this reflective account is to provide a view of the intensive care unit (ICU) relative’s experiences of supporting and being supported in the ICU. Background Understanding the relatives’ experiences of ICU is important especially because a recent work has identified the potential for this group to develop post-traumatic stress disorder, a condition that is normally equated with the ICU survivor. Design A thematic analysis was used in identifying emerging themes that would be significant in an ICU nursing context. Setting The incident took place in two 8-bedded ICUs (Private and National Health Service) in October. Results Two emergent themes were identified from the reflective story – fear of the technological environment and feeling hopeless and helpless. Conclusion The use of relative stories as an insight into the live experiences of ICU relatives may give a deeper understanding of their life-world. The loneliness, anguish and pain of the ICU relative extends beyond the walls of the ICU, and this is often negated as the focus of the ICU team is the patient. Relevance to clinical practice: Developing strategies to support relatives might include the use of relative diaries used concurrently with patient diaries to support this groups recovery or at the very least a gaining a sense of understanding for their ICU experience. Relative follow-up clinics designed specifically to meet their needs where support and advice can be given by the ICU team, in addition to making timely and appropriate referrals to counselling services and perhaps involving spiritual leaders where appropriate.

"Nursing is no place for men" ― A thematic analysis of male nursing students experiences of undergraduate nursing education

Background: Surprisingly, opinion about whether men are suitable within the profession continues to be a divided issue. Men enter the profession for a multitude of reasons, yet barriers whether emotional, verbal or sexual are still present. Aim: The aim of this study was to examine the experience of men “training” to be registered nurses within a regional New Zealand context. Design: A Narrative Analysis approach was used. Participants: Five New Zealand men currently undertaking their bachelor of nursing degree at a regional tertiary institute were interviewed as to their experiences of what it meant to be a man in “training”. Method: A thematic analysis was undertaken and guided by an understanding of the way personal narratives informs the human sciences especially within the context of nursing praxis. Four key themes were identified. Results: Four key themes were identified: A career with flexibility and promise; perceived gender inequality in providing care; developing professional boundaries with female colleagues and being unique has its advantages. Conclusion: The men in this study were attracted to the profession by career stability and advancement; the opportunities for travel also figured highly. At times they felt excluded and marginalised because of their minority status within their group and the feminine nature of the curriculum. The men attempted to dispel the myth around male nurse sexual stereotypes. Some of the students behaved in a manner to exert their heterosexualness. The students in this study sensed their vulnerability in choosing nursing as a career. However, all the participants saw nursing as viable and portable career in terms of advancement and travel.

Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

Tubule detection in testis images using boundary weighting and circular shortest path

In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. © 2013 IEEE.

Calibration of treatment time intensity modulated EPID images for anatomical imaging

Intensity Modulated Radiotherapy (IMRT) is a well established technique for delivering highly conformal radiation dose distributions. The complexity of the delivery techniques and high dose gradients around the target volume make verification of the patient treatment crucial to the success of the treatment. Conventional treatment protocols involve imaging the patient prior to treatment, comparing the patient set-up to the planned set-up and then making any necessary shifts in the patient position to ensure target volume coverage. This paper presents a method for calibrating electronic portal imaging device (EPID) images acquired during IMRT delivery so that they can be used for verifying the patient set-up.

Standardising and assessing digital images for use in clinical trials : a practical, reproducible method that blinds the assessor to treatment allocation

With the increasing availability of high quality digital cameras that are easily operated by the non-professional photographer, the utility of using digital images to assess endpoints in clinical research of skin lesions has growing acceptance. However, rigorous protocols and description of experiences for digital image collection and assessment are not readily available, particularly for research conducted in remote settings. We describe the development and evaluation of a protocol for digital image collection by the non-professional photographer in a remote setting research trial, together with a novel methodology for assessment of clinical outcomes by an expert panel blinded to treatment allocation.

Assessment of the effects of CT dose in averaged x-ray CT images of a dose-sensitive polymer gel

The signal-to-noise ratio achievable in x-ray computed tomography (CT) images of polymer gels can be increased by averaging over multiple scans of each sample. However, repeated scanning delivers a small additional dose to the gel which may compromise the accuracy of the dose measurement. In this study, a NIPAM-based polymer gel was irradiated and then CT scanned 25 times, with the resulting data used to derive an averaged image and a "zero-scan" image of the gel. Comparison between these two results and the first scan of the gel showed that the averaged and zero-scan images provided better contrast, higher contrast-to- noise and higher signal-to-noise than the initial scan. The pixel values (Hounsfield units, HU) in the averaged image were not noticeably elevated, compared to the zero-scan result and the gradients used in the linear extrapolation of the zero-scan images were small and symmetrically distributed around zero. These results indicate that the averaged image was not artificially lightened by the small, additional dose delivered during CT scanning. This work demonstrates the broader usefulness of the zero-scan method as a means to verify the dosimetric accuracy of gel images derived from averaged x-ray CT data.

Corner detection in images under different noise levels

Corner detection has shown its great importance in many computer vision tasks. However, in real-world applications, noise in the image strongly affects the performance of corner detectors. Few corner detectors have been designed to be robust to heavy noise by now, partly because the noise could be reduced by a denoising procedure. In this paper, we present a corner detector that could find discriminative corners in images contaminated by noise of different levels, without any denoising procedure. Candidate corners (i.e., features) are firstly detected by a modified SUSAN approach, and then false corners in noise are rejected based on their local characteristics. Features in flat regions are removed based on their intensity centroid, and features on edge structures are removed using the Harris response. The detector is self-adaptive to noise since the image signal-to-noise ratio (SNR) is automatically estimated to choose an appropriate threshold for refining features. Experimental results show that our detector has better performance at locating discriminative corners in images with strong noise than other widely used corner or keypoint detectors.

When sex doesn't sell: Using sexualized images of women reduces support for ethical campaigns

Images of scantily clad women are used by advertisers to make products more attractive to men. This ‘‘sex sells’’ approach is increasingly employed to promote ethical causes, most prominently by the animal-rights organization PETA. Yet sexualized images can dehumanize women, leaving an unresolved paradox – is it effective to advertise an ethical cause using unethical means? In Study 1, a sample of Australian male undergraduates (N = 82) viewed PETA advertisements containing either sexualized or non-sexualized images of women. Intentions to support the ethical organization were reduced for those exposed to the sexualized advertising, and this was explained by their dehumanization of the sexualized women, and not by increased arousal. Study 2 used a mixed-gender community sample from the United States (N = 280), replicating this finding and extending it by showing that behaviors helpful to the ethical cause diminished after viewing the sexualized advertisements, which was again mediated by the dehumanization of the women depicted. Alternative explanations relating to the reduced credibility of the sexualized women and their objectification were not supported. When promoting ethical causes, organizations may benefit from using advertising strategies that do not dehumanize women.