Grading iris color of post‐mortem human eyes

Background: Despite the presence of various reports regarding the association between iris color and some ocular diseases in adults, there is little evidence of such relation in children. Objectives: Determine the distribution of iris color in seven-year-old children in Iran and its relation with refractive errors, amblyopia, and strabismus. Methods: In this cross-sectional study, 3414 seven-year-old school children were selected from six cities through multistage random sampling. The iris color in this study was classified into dark brown, medium brown, light brown, yellow, green, gray, and blue. All subjects were examined for visual acuity, refraction, and binocular vision assessment. Results: Of the 3414 selected samples, 3030 children participated in the study (89% response rate). The prevalence and 95% confidence intervals (CI) of myopia, hyperopia, and astigmatism was 3.03% (2.30 - 3.99), 6.20% (4.40 - 8.65), and 17.42% (13.30 - 22.48), respectively. Amblyopia was detected in 1.85% (1.10 - 3.12) and the prevalence of strabismus was 2.50% (1.86 - 3.35). Dark brown was the most common iris color at 52.50% (50.06 - 54.93) in boys, 46.07% (43.49 - 48.68) in girls, and 49.50% (47.72 - 51.28) in the total sample population. According to logistic regression results, the odds ratio (95% CI) of hyperopia was 0.3 (0.15 - 0.6) in those with medium brown iris color and 0.23 (0.1 - 0.47) in those with dark brown eyes compared to the group with yellow or green iris colors. Conclusions: Approximately 90% of the studied subjects had dark or medium brown eyes. Given that people with yellow or green eyes are at a higher risk of hyperopia, it is recommended that these individuals be given attention in this regard during screening, and the presence of hyperopia be taken into consideration during refraction examinations for these children.

Use of digital images has increased tremendously in medical science and with that has increased the query on authenticity of the image. Authenticity of the digital image is very important in the area of scientific research, forensic investigations, government documents, etc. With the help of powerful and user friendly image editing software like Microsoft Paint and Photoshop it became extremely easy to tamper with a digital image for malicious objective. Of late this problem has been encountered in medical imaging also for the purpose of fake insurance claims. We propose an algorithm to address this problem by which one can detect and localize tampering in a digital medical image. This algorithm is based on hash based representation of such image and uses discrete wavelet transform method to carry out detection and localization of tampering. We will show that our algorithm is robust against harmless manipulation and sensitive enough for even a minute tampering. Our proposed technique consumes less resource as it works with smaller hash function in comparison with the similar available techniques.

Advances in computer technology continue to bring new innovations to departments of anatomic pathology. This article briefly reviews the present status of digital optical imaging, and explores the directions that this technology may lead over the next several years. Technical requirements for digital microscopic and gross imaging, and the available options for image archival and retrieval are summarized. The advantages of digital images over conventional photography in the conference room, and the usefulness of digital imaging in the frozen section suite and gross room, as an adjunct to surgical signout and as a resource for training and education, are discussed. An approach to the future construction of digital histologic sections and the computer as microscope is described. The digital technologic applications that are now available as components of the surgical pathologist's workstation are enumerated. These include laboratory information systems, computerized voice recognition, and on-line or CD-based literature searching, texts and atlases and, in some departments, on-line image databases. The authors suggest that, in addition to these resources that are already available, tomorrow's surgical pathology workstation will include network-linked digital histologic databases, on-line software for image analysis and 3-D image enhancement, expert systems, and ultimately, advanced pattern recognition capabilities. In conclusion, the authors submit that digital optical imaging is likely to have a significant and positive impact on the future development of anatomic pathology.

Japan has recently introduced the “Audio-Visual Recording of Custodial Interrogation” system to verify the voluntariness of confessions or other disadvantageous statements of the accused that are contained in their depositions. Although digital images recorded in the new system are supposed to be used as supplementary evidence, it appears that they can be used to directly prove the truth of the matter asserted, which is the question to be left open. This article considers whether the digital images can be used to prove guilt or innocence, and if so, whether they need to meet more strict requirements than those for depositions. First, the article discusses the legal grounds pertaining to the application of a conventional hearsay exception to the digital images. Second, it explains how the use of the digital images, which could be concerning, can meet the legal demands of the adversary system underlying the Hearsay Rule. The article concludes that these recordings may be used to prove guilt or innocence if the accused or defense counsels have the meaningful opportunity for impeachment.KeywordsAdmissibilityEvidenceDigital dataInterrogationHearsay

Memory institutions have already started to make digital copies of their documents and objects in order to use modern Information Communications Technologies (ICT) to make their contents easily available. With increasing levels of digitisation, particularly in the cultural heritage sector, the quantity of digital files to be stored very slightly beyond what was produced by Sudanese nation of text processing and much of the hard- and software have been launched or adopted recently. However, there has been little work about the perceptions of SMIs' professionals who are the potential adopters of this technology. Knowledge about such perceptions and their relationship to the application of digital technology by them is important because it can help these professionals to become more aware of the relevance and adaptability technological tools for memory institutions practice. This study focused on these perceptions in regard to the use of a particular technological tool. Its aim was to explore SMIs professionals' perceptions of the ways in which digital collections affect their work, and the reasons why those who don't use digital images or avoid them. To this end, they were asked to describe their use of digital images, the advantages of using digital images, and problems they have faced and to speculate about which impediments need to be overcome in order to begin using digital images. The perspectives of working SMIs professionals on the use digital collections in their institution practice can contribute to our knowledge of how these collections have, and will continue to, influence work. Digital collections cannot be all things to all SMIs professionals. Much debate exists over the role and value of the use of digital images in relation to day-to-day art. The respondents to this study were asked to articulate the potential of digital technology, but this potential is already evidenced by the wide success of distance- researching environments, multimedia projects, animated reconstructions, and research guides in our big multicultural community. In the realm of digital use, many more opportunities await the SMIs profession as related technologies continue to evolve. It is concluded that SMIs constitute local repositories of tacit or explicit contents which will be represented in the digital memory of Sudan (DMS) as an effective gateway to national cultural, historical and heritage image collections of great value to research and development in the country as well as a fully the value of the linkage to global memory net. Finally, the recommendations of this study have been elaborated from UNESCO initiatives in sustainable digital archival and preservation system.

Digital images are routinely used by the publishing industry, but most diagnostic pathologists are unfamiliar with the technology and its possibilities. This review aims to explain the basic principles of digital image acquisition, storage, manipulation and use, and the possibilities provided not only in research, but also in teaching and in routine diagnostic pathology. Images of natural objects are usually expressed digitally as 'bitmaps'--rectilinear arrays of small dots. The size of each dot can vary, but so can its information content in terms, for example, of colour, greyscale or opacity. Various file formats and compression algorithms are available. Video cameras connected to microscopes are familiar to most pathologists; video images can be converted directly to a digital form by a suitably equipped computer. Digital cameras and scanners are alternative acquisition tools of relevance to pathologists. Once acquired, a digital image can easily be subjected to the digital equivalent of any conventional darkroom manipulation and modern software allows much more flexibility, to such an extent that a new tool for scientific fraud has been created. For research, image enhancement and analysis is an increasingly powerful and affordable tool. Morphometric measurements are, after many predictions, at last beginning to be part of the toolkit of the diagnostic pathologist. In teaching, the potential to create dramatic yet informative presentations is demonstrated daily by the publishing industry; such methods are readily applicable to the classroom. The combination of digital images and the Internet raises many possibilities; for example, instead of seeking one expert diagnostic opinion, one could simultaneously seek the opinion of many, all around the globe. It is inevitable that in the coming years the use of digital images will spread from the laboratory to the medical curriculum and to the whole of diagnostic pathology.

Chapter 10 - Digital Imaging Technologies

The use of digital images could be a faster and cheaper alternative technique to assess BW, HCW, and body composition of beef cattle. The objective of this study was to develop equations to predict body and carcass weight and body fat content of young bulls using digital images obtained through a Microsoft Kinect device. Thirty-five bulls with an initial BW of 383 (±5.38) kg (20 Black Angus, 390 [±7.48] kg initial BW, and 15 Nellore, 377 [±8.66] kg initial BW) were used. The Kinect sensor, installed on the top of a cattle chute, was used to take infrared light-based depth videos, recorded before the slaughter. For each animal, a quality control was made, running and pausing the video at the moment that the animal was standing with its body and head in line. One frame from recorded videos was selected and used to analyze the following body measurements: chest width, thorax width, abdomen width, body length, dorsal height, and dorsal area. From these body measurements, 23 indexes were generated and tested as potential predictors. The BW and HCW were assessed with a digital scale, whereas empty body fat (EBF) was estimated through ground samples of all tissues. To better understand the relationship among the measurements, the correlations between final BW (488 [±10.4] kg), HCW (287 [±12.5] kg), EBF (14 [±0.610] % empty BW) content, body measurements (taken through digital images), and developed indexes were evaluated. The REG procedure was used to develop the regressions, and the important independent variables were identified using the options STEPWISE and Mallow's Cp in the SELECTION statement. Chest width was the trait most related to weights and the correlations between this measurement and BW and HCW were above 0.85. The analysis of linear regressions between observed and predicted values showed that all models pass through the origin and have a slope of unity (null hypothesis [H]: = 0 and = 1; ≥ 0.993). The models to estimate BW and HCW of Angus and Nellore presented between 0.69 and 0.84 ( < 0.001), whereas from equations to estimate the EBF were lower ( = 0.43-0.45; ≤ 0.006). Index I5 [(chest width) × body length], related to the animal volume, was significant in all models created to estimate BW and HCW, and it explained more than 70% of the variation. This study indicates that digital images taken through a Microsoft Kinect system have the potential to be used as a tool to estimate body and carcass weight of beef cattle.

An alternative approach for soil characterization is proposed, using digital images and machine learning. The present work investigated the Red, Green, and Blue (RGB) pattern with Artificial Neural Network (ANN) and Random Forest (RF) in the classification of Oxisol and Inceptisol collected in South Brazil. Furthermore, we also built ANN, RF, Partial Least Squares (PLS), and Support Vector Machine (SVM) models from digital images to quantify Total Carbon (TC) content in soil samples. Preliminary evaluations considered the hypothesis that alternative methods of classification and quantification of soil properties might provide results comparable to traditional methods. The TC content of 91 soil samples, 40 from Oxisol and 51 from Inceptisol were determined by dry combustion. ANN and RF as machine learning algorithms were applied to classify the two kinds of soils. The classification quality was assessed by the percentage of correctly classified instances. The results suggest using digital images and machine learning algorithms as a new methodology to soil classification. The best machine learning method was RF which can be used to classify soil types by the RGB channel colors of the soil images. The use of digital images and RF is a clean (eco-friendly), rapid, and affordable strategy analysis for TC quantification in soils. Therefore, the proposed methods represent an advancement in soil classification, such as the determination of the TC content of soils.

Digital Image Security is one of the most important information security topics today. Along with the increasing use of digital images both for communication and documentation purposes, the security of information contained in digital images needs serious attention. Rijndael is a cryptographic method that is not only used for text encryption but also for digital image encryption. Just like block-based cryptographic methods in general, encoding data bytes only has an effect on the internal environment of the block, because the transformation process in Rijndael is done separately for each input block. In digital images, this can result in visible patterns or shapes of objects contained in the image, especially when using the Rijndael standard block size of 4x4. To improve the quality of digital image encryption on Rijndael, several studies have made modifications, especially at the transformation stage. In terms of data, the statistical values obtained from the encryption results such as the correlation coefficient do show an increase, but visually the pattern of objects is still visible and modifications tend to be high. This research proposes a modification of Rijndael which focuses on increasing the input block size from 4x4 to 8x8 with minimal changes to the transformation function. The results showed that the value of the correlation coefficient was better and the results of the encryption visually disguised the shape of the object more than the usual Rijndael, especially in text images, logos and caricatures. From the process carried out there is an increase in the quality of security for the encryption process by 13.22% to 91.48%.

Caveat Spectator: Digital Imaging and Data Manipulation

The purpose of this study is to determine the association between corneal sensitivity measured using a pneumatic esthesiometer and eye color quantified objectively. Twenty subjects had ocular surface sensitivity measured using a Belmonte esthesiometer. An ascending method of limits followed by the method of constant stimuli were used to estimate 1) cold detection thresholds, 2) discomfort detection thresholds (both using pneumatic stimuli at 20 degrees C, 3) mechanical detection thresholds using pneumatic stimuli at 50 degrees C (ocular surface temperature approximately 33 degrees C), and 4) percent CO2 chemical detection thresholds using 50 degrees C pneumatic stimuli at flow rates set at half of each subject's pneumatic detection threshold (therefore detected by the chemical content and not the mechanical content). Eye color was estimated 1) clinically by two observers ranking the color (light to dark) of digital images of each subject's iris, 2) photometrically by measuring iris luminance, and 3) using chromaticity obtained from a Photo Research 650 spectroradiometer with controlled illumination. Correlation and linear and nonlinear regression analyses were used to examine relationships between variables. There were no associations between eye color (determined clinically or objectively) for mechanical and chemical detection thresholds (best r = 0.15, all p > 0.05). There was a significant linear association between 20 degrees detection thresholds and eye color (r = 0.39), which was substantially improved with a two-line function (part level and part increasing linearly, r = 0.65). We were generally unable to demonstrate the relationship between eye color and sensitivity reported previously using a Cochet-Bonnet esthesiometer. However, for a subset of subjects with palest irises, there appears to be a linear association between eye color and sensitivity to cooling stimuli.

Digital images are convenient and important media for describing and storing spatial, temporal, spectral, and physical components of information contained in a variety of domains. With the progress of electronics, sensors, computer equipment, and network infrastructure, today’s technology enables us to generate, acquire, manipulate, transmit, and store vast (online) image collections. The applications of images, which are expanding over wider and wider areas, have attracted more and more attention in recent years. The use of digital images in teaching and learning is one of the popular application areas.

The purpose of this study was to evaluate homecare nurses' knowledge of wound assessment using digital images and case studies. A descriptive design was used. Subjects were a convenience sample of 33 registered nurses from a Washington, DC, metropolitan-based home health agency. Participants were asked to complete a demographic data sheet and a wound assessment checklist, while viewing projected digital images of 10 different wounds. A case study accompanied each image and provided wound assessment data that could not be visualized. Frequencies were calculated to determine the percentage of homecare nurses who were accurate in their assessment. The most common error in staging was a lack of recognition of wounds that were not stageable. The majority of the homecare nurses were able to accurately identify wound bed and periwound characteristics; the greatest variability was found in the ratings for wound bed color. Despite the difficulty of interpreting digital images of wounds, the study findings support the value of using them to evaluate nurses' knowledge of the visual aspects of wound assessment as a basis for educational programs.

Classification of sugar using digital imaging and pattern recognition techniques