Glaucoma Expert-Level Detection of Angle Closure in Goniophotographs With Convolutional Neural Networks: The Chinese American Eye Study.

PURPOSE: To compare the performance of a novel convolutional neural network (CNN) classifier and human graders in detecting angle closure in EyeCam (Clarity Medical Systems, Pleasanton, California, USA) goniophotographs. DESIGN: Retrospective cross-sectional study. METHODS: Subjects from the Chinese American Eye Study underwent EyeCam goniophotography in 4 angle quadrants. A CNN classifier based on the ResNet-50 architecture was trained to detect angle closure, defined as inability to visualize the pigmented trabecular meshwork, using reference labels by a single experienced glaucoma specialist. The performance of the CNN classifier was assessed using an independent test dataset and reference labels by the single glaucoma specialist or a panel of 3 glaucoma specialists. This performance was compared to that of 9 human graders with a range of clinical experience. Outcome measures included area under the receiver operating characteristic curve (AUC) metrics and Cohen kappa coefficients in the binary classification of open or closed angle. RESULTS: The CNN classifier was developed using 29,706 open and 2,929 closed angle images. The independent test dataset was composed of 600 open and 400 closed angle images. The CNN classifier achieved excellent performance based on single-grader (AUC = 0.969) and consensus (AUC = 0.952) labels. The agreement between the CNN classifier and consensus labels (κ = 0.746) surpassed that of all non-reference human graders (κ = 0.578-0.702). Human grader agreement with consensus labels improved with clinical experience (P = 0.03). CONCLUSION: A CNN classifier can effectively detect angle closure in goniophotographs with performance comparable to that of an experienced glaucoma specialist. This provides an automated method to support remote detection of patients at risk for primary angle closure glaucoma.

Universal adversarial attacks on deep neural networks for medical image classification.

BACKGROUND: Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks, as high-stake decision-making will be made based on the diagnosis. Several previous studies have considered simple adversarial attacks. However, the vulnerability of DNNs to more realistic and higher risk attacks, such as universal adversarial perturbation (UAP), which is a single perturbation that can induce DNN failure in most classification tasks has not been evaluated yet. METHODS: We focus on three representative DNN-based medical image classification tasks (i.e., skin cancer, referable diabetic retinopathy, and pneumonia classifications) and investigate their vulnerability to the seven model architectures of UAPs. RESULTS: We demonstrate that DNNs are vulnerable to both nontargeted UAPs, which cause a task failure resulting in an input being assigned an incorrect class, and to targeted UAPs, which cause the DNN to classify an input into a specific class. The almost imperceptible UAPs achieved > 80% success rates for nontargeted and targeted attacks. The vulnerability to UAPs depended very little on the model architecture. Moreover, we discovered that adversarial retraining, which is known to be an effective method for adversarial defenses, increased DNNs' robustness against UAPs in only very few cases. CONCLUSION: Unlike previous assumptions, the results indicate that DNN-based clinical diagnosis is easier to deceive because of adversarial attacks. Adversaries can cause failed diagnoses at lower costs (e.g., without consideration of data distribution); moreover, they can affect the diagnosis. The effects of adversarial defenses may not be limited. Our findings emphasize that more careful consideration is required in developing DNNs for medical imaging and their practical applications.

Grading Diabetic Retinopathy from Stereoscopic Color Fundus Photographs - An Extension of the Modified Airlie House Classification: ETDRS Report Number 10.

The modified Airlie House classification of diabetic retinopathy has been extended for use in the Early Treatment Diabetic Retinopathy Study (ETDRS). The revised classification provides additional steps in the grading scale for some characteristics, separates other characteristics previously combined, expands the section on macular edema, and adds several characteristics not previously graded. The classification is described and illustrated and its reproducibility between graders is assessed by calculating percentages of agreement and kappa statistics for duplicate gradings of baseline color non- simultaneous stereoscopic fundus photographs. For retinal hemorrhages and/ or microaneurysms, hard exudates, new vessels, fibrous proliferations, and macular edema, agreement was substantial (weighted kappa, 0.61 to 0.80). For soft exudates, intraretinal microvascular abnormalities, and venous beading, agreement was moderate (weighted kappa, 0.41 to 0.60). A double grading system, with adjudication of disagreements of two or more steps between duplicate gradings, led to some improvement in reproducibility for most characteristics.

Hierarchical Approach to Classify Food Scenes in Egocentric Photo-Streams.

Recent studies have shown that the environment where people eat can affect their nutritional behavior [1]. In this paper, we provide automatic tools for personalized analysis of a person's health habits by the examination of daily recorded egocentric photo-streams. Specifically, we propose a new automatic approach for the classification of food-related environments, that is able to classify up to 15 such scenes. In this way, people can monitor the context around their food intake in order to get an objective insight into their daily eating routine. We propose a model that classifies food-related scenes organized in a semantic hierarchy. Additionally, we present and make available a new egocentric dataset composed of more than 33 000 images recorded by a wearable camera, over which our proposed model has been tested. Our approach obtains an accuracy and F-score of 56% and 65%, respectively, clearly outperforming the baseline methods.

SURGICAL OUTCOMES OF MYOPIC TRACTION MACULOPATHY ACCORDING TO THE INTERNATIONAL PHOTOGRAPHIC CLASSIFICATION FOR MYOPIC MACULOPATHY.

PURPOSE: To compare treatment results of myopic traction maculopathy according to the international photographic classification for myopic maculopathy. METHODS: This was a retrospective, single-surgeon-based, observational case series of 35 consecutive eyes that underwent vitrectomy for myopic traction maculopathy. Eyes were classified into nonpathologic myopia (PM) (n = 15) and PM (n = 20) groups. Main outcome measures constituted best-corrected visual acuity (BCVA) and anatomical change. RESULTS: The mean follow-up was 32.03 ± 6.85 months. Axial length correlated with myopic maculopathy category (rho = 0.6836, P < 0.001). In the total group, BCVA improved from 20/61 to 20/36 (P = 0.001). In the subgroup, BCVA improved from 20/41 to 20/22 in the non-PM group (P = 0.002), whereas from 20/82 to 20/52 in the PM group (P = 0.048). Postoperative BCVA of the PM group was inferior to that of the non-PM group (P = 0.002) and the PM group was more likely to have postoperative BCVA <20/30 (odds ratio, 17.3; 95% CI, 2.6-325.0; P = 0.012). Two cases of macular hole retinal detachment occurred after surgery in the PM group. CONCLUSION: Because there are limited benefits of vitrectomy in myopic traction maculopathy accompanied by PM, careful consideration would be necessary when determining surgery. Optical coherence tomography should not be used alone in determining vitrectomy because myopic traction maculopathy can also have PM defined mainly by fundus photographs.

Accuracy of trained rural ophthalmologists versus non-medical image graders in the diagnosis of diabetic retinopathy in rural China.

BACKGROUND/AIMS: To determine the diagnostic accuracy of trained rural ophthalmologists and non-medical image graders in the assessment of diabetic retinopathy (DR) in rural China. METHODS: Consecutive patients with diabetes mellitus were examined from January 2014 to December 2015 at 10 county-level facilities in rural Southern China. Trained rural ophthalmologists performed a complete eye examination, recording diagnoses using the UK National Diabetic Eye Screening Programme (NDESP) classification system. Two field, mydriatic, 45° digital photographs were made by nurses using NDESP protocols and graded by trained graders with no medical background using the NDESP system. A fellowship-trained retina specialist graded all images in masked fashion and served as reference standard. RESULTS: Altogether, 375 participants (mean age 60±10 years, 48% men) were examined and 1277 images were graded. Grader sensitivity (0.82-0.94 (median 0.88)) and specificity (0.91-0.99 (median 0.98)), reached or exceeded NDESP standards (sensitivity 80%, specificity 95%) in all domains except specificity detecting any DR. Rural ophthalmologists' sensitivity was 0.65-0.95 (median 0.66) and specificity 0.59-0.95 (median 0.91). There was strong agreement between graders and the reference standard (kappa=0.84-0.87, p<0.001) and weak to moderate agreement between rural doctors and the reference (kappa=0.48-0.64, p<0.001). CONCLUSION: This is the first study of diagnostic accuracy in DR grading among non-medical graders or ophthalmologists in low-income and middle-income countries. Non-medical graders can achieve high levels of accuracy, whereas accuracy of trained rural ophthalmologists is not optimal.

Validity of a new comprehensive pterygia grading scale for use in clinical research and clinical trial.

PURPOSE: To determine the reliability and agreement of a new comprehensive pterygium grading scale for use in clinical research and clinical trials. METHODS: Thirty eyes with pterygia were enrolled in this study. Primary gaze position and lateral gaze position images were taken of each eye with a modified single-lens reflex camera system. Our grading scale includes five parameters: two hyperemia parameters of pterygia on two different gaze position images and three size parameters, quantifying length, width, and area of the cornea encroachment of pterygium, using ImageJ software. All images were graded on the five parameters by two masked, certified reading center graders. Two graders independently graded all the images to determine inter-grader reliability. One grader regraded the images after 3 days to determine intra-grader reliability. Intraclass correlation coefficient (ICC) and inter-rater agreement statistic (κ) calculations were performed. RESULTS: The intra-grader reliability for hyperemia grading was high on both primary and lateral gazing positions (κ value is 0.93 and 0.96). The inter-grader reliability for hyperemia grading was also good (κ value is 0.85 and 0.87). The mean value of width, length, and area of the cornea encroachment of pterygium was 4.31 ± 2.04 mm, 2.08 ± 1.43 mm, and 7.84 ± 7.62 mm2, respectively. The intra-grader agreement on width, length, and area were excellent, with ICCs of 0.98 (95% CI 0.96-0.99), 0.99 (95% CI 0.98-1.0), and 0.97 (95% CI 0.94-0.99), respectively. The inter-grader agreement on width, length, and area were also excellent, with ICCs of 0.96 (95% CI 0.90-0.98), 0.99 (95% CI 0.98-0.99), and 0.99 (95% CI 0.97-0.99), respectively. CONCLUSIONS: There was excellent intra- and inter-observer reproducibility with the new comprehensive grading scale. This scale could lead to the development of standardized grading assessments and quantification of pterygia that would be valid in clinical research and clinical trials.

BMC ecology image competition 2017: the winning images.

For the fifth year, BMC Ecology is proud to present the winning images from our annual image competition. The 2017 edition received entries by talented shutterbug-ecologists from across the world, showcasing research that is increasing our understanding of ecosystems worldwide and the beauty and diversity of life on our planet. In this editorial we showcase the winning images, as chosen by our Editorial Board and guest judge Chris Darimont, as well as our selection of highly commended images. Enjoy!

The grey fovea sign of macular oedema or subfoveal fluid on non-stereoscopic fundus photographs.

PURPOSE: To describe the grey fovea sign of fovea-involving macular oedema or subretinal fluid accumulation in red-free fundus photography. METHODS: A test set of 91 digital fundus photographs of good quality from 100 consecutive eyes in 72 patients with diabetic retinopathy or central serous chorioretinopathy was composed by one of the investigators and evaluated by four masked observers. The photographs were graded as to whether a normal dark fovea was present or absent. The reference method was foveal thickness measurement using optical coherence tomography (OCT). RESULTS: Eyes graded as having a grey fovea on fundus photographs (n = 67) had a median foveal thickness of 279 µm (interquartile range 130 µm), whereas eyes graded as having a normal dark fovea (n = 24) had a median foveal thickness of 238 µm (interquartile range 44.5 µm, p = 0.025). CONCLUSION: The absence of a dark fovea on red-free greyscale fundus photographs is a sign of foveal thickening or detachment that can be reliably recognized by graders when using OCT as the reference diagnostic method. Awareness of the grey fovea sign may facilitate fundus photographic screening for maculopathy because its absence is a reliable sign that no foveal oedema or detachment is present. Its presence may indicate that such conditions are present, but it can also be induced by various other conditions, for which reason it should prompt further investigations by OCT.

Identification of Diabetic Retinopathy and Ungradable Image Rate with Ultrawide Field Imaging in a National Teleophthalmology Program.

PURPOSE: To compare diabetic retinopathy (DR) identification and ungradable image rates between nonmydriatic ultrawide field (UWF) imaging and nonmydriatic multifield fundus photography (NMFP) in a large multistate population-based DR teleophthalmology program. DESIGN: Multiple-site, nonrandomized, consecutive, cross-sectional, retrospective, uncontrolled imaging device evaluation. PARTICIPANTS: Thirty-five thousand fifty-two eyes (17 526 patients) imaged using NMFP and 16 218 eyes (8109 patients) imaged using UWF imaging. METHODS: All patients undergoing Joslin Vision Network (JVN) imaging with either NMFP or UWF imaging from May 1, 2014, through August 30, 2015, within the Indian Health Service-JVN program, which serves American Indian and Alaska Native communities at 97 sites across 25 states, were evaluated. All retinal images were graded using a standardized validated protocol in a centralized reading center. MAIN OUTCOME MEASURES: Ungradable rate for DR and diabetic macular edema (DME). RESULTS: The ungradable rate per patient for DR and DME was significantly lower with UWF imaging compared with NMFP (DR, 2.8% vs. 26.9% [P < 0.0001]; DME, 3.8% vs. 26.2% [P < 0.0001]). Identification of eyes with either DR or referable DR (moderate nonproliferative DR or DME or worse) was increased using UWF imaging from 11.7% to 24.2% (P < 0.0001) and from 6.2% to 13.6% (P < 0.0001), respectively. In eyes with DR imaged with UWF imaging (n = 3926 eyes of 2402 patients), the presence of predominantly peripheral lesions suggested a more severe level of DR in 7.2% of eyes (9.6% of patients). CONCLUSIONS: In a large, widely distributed DR ocular telehealth program, as compared with NMFP, nonmydriatic UWF imaging reduced the number of ungradable eyes by 81%, increased the identification of DR nearly 2-fold, and identified peripheral lesions suggesting more severe DR in almost 10% of patients, thus demonstrating significant benefits of this imaging method for large DR teleophthalmology programs.

Evaluation of Nonmydriatic Hand-held Optic Disc Photography Grading in the Philadelphia Glaucoma Detection and Treatment Project.

PURPOSE: To determine the reproducibility of optic disc photograph grading obtained by a hand-held fundus camera and to determine the diagnostic value of these photographs in detecting patients with glaucoma in a community-based glaucoma-detection program. MATERIALS AND METHODS: Patients underwent slit-lamp examination by an ophthalmologist who graded each patient's optic discs using 2 methods: cup-to-disc ratio (CDR) and disc damage likelihood scale (DDLS). After a comprehensive glaucoma evaluation, patients were diagnosed as having "glaucoma," "glaucoma suspect," or "no glaucoma." Nonmydriatic, monoscopic optic disc photographs were then taken with a portable digital imaging device. On a different day, the same examiner and a second observer graded the disc photographs in a masked manner and determined a diagnostic impression based only on the disc photographs. RESULTS: Of the 1649 patients examined, 119 subjects were randomly selected according to 3 groups of diagnoses: "glaucoma" (n=36), "glaucoma suspect" (n=50), and "no glaucoma" (n=33). For CDR, the intraobserver agreement was 0.71 and the interobserver agreement was 0.69. For disc DDLS, the intraobserver agreement was 0.65 and the interobserver agreement was 0.67. The area under the receiver-operating characteristic distinguishing between normal and glaucoma was 0.88 and 0.86 for CDR and disc DDLS, respectively. CONCLUSIONS: Nonmydriatic, monoscopic disc photographs obtained by a hand-held camera had only moderate disc grading reproducibility. This could be due to a reduced quality of images, making interpretation more challenging, due to taking photographs through small pupils by a hand-held camera and the high percentage of patients with significant cataracts.

Agreement between novice and experienced trachoma graders improves after a single day of didactic training.

BACKGROUND/AIMS: Prevalence estimates and treatment decisions for trachoma are based entirely on ocular clinical examination. The aim of the current study is to demonstrate that ophthalmic assistants can be trained and certified to provide trachoma grading within a single day. METHODS: Conjunctival photographs from an area with endemic trachoma were randomised into two sets of 60 cases. Photographs were graded for trachomatous inflammation-follicular (TF) and trachomatous inflammation-intense (TI) by three experienced graders. Inter-rater reliability of eight ophthalmic assistants and three experienced graders were compared before and after training. RESULTS: The mean κ agreement between the ophthalmic assistants and the consensus grades of the experienced graders for TF was 0.38 (95% CI 0.18 to 0.58) before training, and increased to 0.60 (95% CI 0.42 to 0.78) after training (p=0.07). The mean κ agreement for TI was 0.16 (95% CI 0.02 to 0.30) before training, and increased to 0.39 (95% CI 0.20 to 0.58) after training (p=0.02). CONCLUSION: A single day of training improves agreement between prospective and experienced trachoma graders, and provides the basis for certification of workers who are able to accurately grade trachoma and generate reliable prevalence estimates.

Inter-Rater Agreement between Trachoma Graders: Comparison of Grades Given in Field Conditions versus Grades from Photographic Review.

PURPOSE: Trachoma surveillance is most commonly performed by direct observation, usually by non-ophthalmologists using the World Health Organization (WHO) simplified grading system. However, conjunctival photographs may offer several benefits over direct clinical observation, including the potential for greater inter-rater agreement. This study assesses whether inter-rater agreement of trachoma grading differs when trained graders review conjunctival photographs compared to when they perform conjunctival examinations in the field. METHODS: Three trained trachoma graders each performed an independent examination of the everted right tarsal conjunctiva of 269 children aged 0-9 years, and then reviewed photographs of these same conjunctivae in a random order. For each eye, the grader documented the presence or absence of follicular trachoma (TF) and intense trachomatous inflammation (TI) according to the WHO simplified grading system. RESULTS: Inter-rater agreement for the grade of TF was significantly higher in the field (kappa coefficient, κ, 0.73, 95% confidence interval, CI 0.67-0.80) than by photographic review (κ = 0.55, 95% CI 0.49-0.63; difference in κ between field grading and photo grading 0.18, 95% CI 0.09-0.26). When field and photographic grades were each assessed as the consensus grade from the three graders, agreement between in-field and photographic graders was high for TF (κ = 0.75, 95% CI 0.68-0.84). CONCLUSIONS: In an area with hyperendemic trachoma, inter-rater agreement was lower for photographic assessment of trachoma than for in-field assessment. However, the trachoma grade reached by a consensus of photographic graders agreed well with the grade given by a consensus of in-field graders.

RETINAL ANGIOMATOUS PROLIFERATION: A Quantitative Analysis of the Fundoscopic Features of the Fellow Eye.

PURPOSE: To quantitatively analyze and compare the fundoscopic features between fellow eyes of retinal angiomatous proliferation and typical exudative age-related macular degeneration and to identify possible predictors of neovascularization. METHODS: Retrospective case-control study. Seventy-nine fellow eyes of unilateral retinal angiomatous proliferation (n = 40) and typical exudative age-related macular degeneration (n = 39) were included. Fundoscopic features of the fellow eyes were assessed using digital color fundus photographs taken at the time of diagnosis of neovascularization in the first affected eye. Grading was performed by two independent graders using RetmarkerAMD, a computer-assisted grading software based on the International Classification and Grading System for age-related macular degeneration. RESULTS: Baseline total number and area (square micrometers) of drusen in the central 1,000, 3,000, and 6,000 µm were considerably inferior in the fellow eyes of retinal angiomatous proliferation, with statistically significant differences (P < 0.05) observed in virtually every location (1,000, 3,000, and 6,000 µm). A soft drusen (≥125 µm) area >510,196 µm2 in the central 6,000 µm was associated with an increased risk of neovascularization (hazard ratio, 4.35; 95% confidence interval [1.56-12.15]; P = 0.005). CONCLUSION: Baseline fundoscopic features of the fellow eye differ significantly between retinal angiomatous proliferation and typical exudative age-related macular degeneration. A large area (>510,196 µm2) of soft drusen in the central 6,000 µm confers a significantly higher risk of neovascularization and should be considered as a phenotypic risk factor.

Covert photo classification by fusing image features and visual attributes.

In this paper, we study a novel problem of classifying covert photos, whose acquisition processes are intentionally concealed from the subjects being photographed. Covert photos are often privacy invasive and, if distributed over Internet, can cause serious consequences. Automatic identification of such photos, therefore, serves as an important initial step toward further privacy protection operations. The problem is, however, very challenging due to the large semantic similarity between covert and noncovert photos, the enormous diversity in the photographing process and environment of cover photos, and the difficulty to collect an effective data set for the study. Attacking these challenges, we make three consecutive contributions. First, we collect a large data set containing 2500 covert photos, each of them is verified rigorously and carefully. Second, we conduct a user study on how humans distinguish covert photos from noncovert ones. The user study not only provides an important evaluation baseline, but also suggests fusing heterogeneous information for an automatic solution. Our third contribution is a covert photo classification algorithm that fuses various image features and visual attributes in the multiple kernel learning framework. We evaluate the proposed approach on the collected data set in comparison with other modern image classifiers. The results show that our approach achieves an average classification rate (1-EER) of 0.8940, which significantly outperforms other competitors as well as human's performance.

International photographic classification and grading system for myopic maculopathy.

PURPOSE: To develop a classification and grading system for myopic maculopathy. DESIGN: Development and evaluation of a classification system for myopic maculopathy based on observational case series. METHODS: A comprehensive set of myopic macular lesions was defined via literature review and through consensus meetings among retinal specialists and clinician scientists. A classification of myopic maculopathy was formulated based on fundus photographs and a modified Delphi process and consensus. Inter- and intraobserver reproducibility, assessed as agreement (%) and weighted kappa values, were evaluated. One hundred retinal photographs with myopia and myopic macular lesions were selected from case series at the High Myopia Clinic of the Tokyo Medical and Dental University, Tokyo, Japan. RESULTS: We defined 5 categories of myopic maculopathy including "no myopic retinal degenerative lesion" (Category 0), "tessellated fundus" (Category 1), "diffuse chorioretinal atrophy" (Category 2), "patchy chorioretinal atrophy" (Category 3), and "macular atrophy" (Category 4). Three additional features to supplement these categories were defined as "plus" lesions, namely, lacquer cracks, myopic choroidal neovascularization, and Fuchs spot. Posterior staphyloma was considered as a further, important sign of myopic retinopathy. The intraobserver agreement was ≥85% and the corresponding weighted kappa statistic was ≥0.6 between observations. After a brief training session, interobserver kappa statistics reached the predefined satisfactory level (≥0.4), considered as above moderate agreement. CONCLUSIONS: We propose a classification system for myopic maculopathy that was found to be reproducible. Applying a uniform classification in different studies will facilitate communication and comparison of findings from clinical trials and epidemiologic studies.

Telemedicine diagnosis of cytomegalovirus retinitis by nonophthalmologists.

IMPORTANCE: Cytomegalovirus (CMV) retinitis continues to be a leading cause of blindness in many developing countries. Telemedicine holds the potential to increase the number of people screened for CMV retinitis, but it is unclear whether nonophthalmologists could be responsible for interpreting fundus photographs captured in a telemedicine program. OBJECTIVE: To determine the accuracy of nonophthalmologist photographic graders in diagnosing CMV retinitis from digital fundus photographs. DESIGN, SETTING, AND PARTICIPANTS: Fifteen nonexpert graders each evaluated 182 mosaic retinal images taken from the eyes of patients with AIDS who were evaluated at the Ocular Infectious Diseases Clinic at Chiang Mai University in Chiang Mai, Thailand. MAIN OUTCOMES AND MEASURES: Graders diagnosed each image as CMV retinitis present, CMV retinitis absent, or unknown. The results from each grader were compared with those of an indirect ophthalmoscopic examination from an experienced on-site ophthalmologist as well as with the consensus grade given by a panel of CMV retinitis experts. RESULTS: Relative to the on-site ophthalmologist, the sensitivity of remote CMV retinitis diagnosis by nonexpert graders ranged from 64.0% to 95.5% (mean, 84.1%; 95% CI, 78.6%-89.6%)), and the specificity ranged from 65.6% to 92.5% (mean, 82.3%; 95% CI, 76.6%-88.0%)). Agreement between nonexpert and expert graders was high: the mean sensitivity and specificity values of nonexpert diagnosis using expert consensus as the reference standard were 93.2% (95% CI, 90.6%-95.8%) and 88.4% (95% CI, 85.4%-91.1%), respectively. Mean intrarater reliability also was high (mean Cohen κ, 0.83; 95% CI, 0.78-0.87). CONCLUSIONS AND RELEVANCE: The sensitivity and specificity of remote diagnosis of CMV retinitis by nonexpert graders was variable, although several nonexperts achieved a level of accuracy comparable to that of CMV retinitis experts. More intensive training and periodic evaluations would be required if nonexperts are to be used in clinical practice.

How do people order stimuli?

People may find it easier to construct an order after first representing stimuli on a scale or categorizing them, particularly when the number of stimuli to be ordered is large or when some of them must be remembered. Five experiments tested this hypothesis. In two of these experiments (1 and 3), we asked participants to rank line lengths or to rank photographs by artistic value. The participants provided evidence of how they performed these tasks, and this evidence indicated that they often made use of some preliminary representation--either a metric or a categorization. Two further experiments (2 and 4) indicated that people rarely produced rankings when given a choice of assessment measures for either the length of lines or the artistic value of photographs. In Experiment 5, when the number of lines was larger or lines were only visible one at a time, participants were faster at estimating line lengths as a percentage of the card covered than at rank ordering the lengths. Overall, the results indicate that ordering stimuli is not an easy or natural process when the number of stimuli is large or when the stimuli are not all perceptible at once. An implication is that the psychological measures available to individuals are not likely to be purely ordinal when many of the elements being measured must be recalled.

Applying a verification classification system to medical and forensic digital images.

This paper gives the definitions, and describes the application, of a classification system for photographic veracity relating to medical and forensic images. It uses practical examples to demonstrate the reasons and parameters for using such a system. It also calls for continued discussion on what the limits and extent should be for the parameters. A debate encompassing the advantages and disadvantages of manipulating photographs goes back well before the introduction of digital imaging and has continued since the introduction of photography in the mid-nineteenth century. This author's first foray dates back twenty years (1). The introduction of digital imaging only gave the debate new impetus and new problems to solve (2), some of which might be resolved as suggested in this paper.

Measuring streetscape complexity based on the statistics of local contrast and spatial frequency.

Streetscapes are basic urban elements which play a major role in the livability of a city. The visual complexity of streetscapes is known to influence how people behave in such built spaces. However, how and which characteristics of a visual scene influence our perception of complexity have yet to be fully understood. This study proposes a method to evaluate the complexity perceived in streetscapes based on the statistics of local contrast and spatial frequency. Here, 74 streetscape images from four cities, including daytime and nighttime scenes, were ranked for complexity by 40 participants. Image processing was then used to locally segment contrast and spatial frequency in the streetscapes. The statistics of these characteristics were extracted and later combined to form a single objective measure. The direct use of statistics revealed structural or morphological patterns in streetscapes related to the perception of complexity. Furthermore, in comparison to conventional measures of visual complexity, the proposed objective measure exhibits a higher correlation with the opinion of the participants. Also, the performance of this method is more robust regarding different time scenarios.