Mobile Digital Imaging Research Articles

Differences in Perceptual and Attitudinal Body Image Between White and African-American Adults Matched for Sex, Age, and Body Composition.

The purpose of this study was to evaluate the differences in perceptual and attitudinal body image between White and African-American males and females matched for sex, age, BMI, and other body composition components using a combination of 3-dimensional mobile digital imaging analysis (DIA) and the Multidimensional Body-Self Relations Questionnaire-Appearance Scale (MBSRQ-AS). One-hundred non-Hispanic White (n=50) and non-Hispanic African-American (n=50) adults (M=34, F=66) matched for sex, age, BMI, and body composition components completed this cross-sectional study. Participants underwent several anthropometric assessments, completed the MBSRQ-AS, and rated their perceived appearance, ideal appearance, and the appearance they believed a partner would find societally attractive using a state of the art mobile 3-dimensional DIA produced using broad developmental populations. Body image distortion was measured as the perceived minus actual appearance, and body image dissatisfaction was defined as the ideal appearance and appearance a partner would find attractive minus the perceived appearance. Using the DIA, only African-American females demonstrated significant body image distortion (p<0.001); reporting perceived appearances significantly lower their than their actual. Further, AA females demonstrated significantly larger differences between their ideal and perceived appearance (p=0.009), perceived larger bodies as more attractive to a potential partner (p=0.009), and reported higher ratings of appearance evaluation (p=0.001) and body area satisfaction (p=0.011) compared to White females. After accounting for all anthropometric determinants of body image, perceptual and attitudinal body image differs between White and African-American adults with differences supporting larger body size acceptance for African-American individuals, particularly African-American females.

Validation of a Novel Perceptual Body Image Assessment Method Using Mobile Digital Imaging Analysis: A Cross-Sectional Multicenter Evaluation in a Multiethnic Sample

Given that mobile digital imaging analyses (DIA) are equipped to automate body composition and subsequently alter one’s appearance at a given objective body fat percent (BF%), the purpose of this study was to validate the use of this tool for assessments of body image. Participants (f = 134, m = 89) from two separate centers underwent body composition scans using a mobile DIA and completed the Multidimensional Body Self-Relations Questionnaire–Appearance Scale (MBSRQ-AS). Using a DIA-generated avatar, participants altered their figure so that it represented their perceived body, ideal body, and what a partner would find attractive. Distortion was calculated as perceived minus actual BF% and dissatisfaction was calculated as either ideal or partner minus perceived BF%. The total sample and females (p < 0.050), but not males, had significantly lower perceived BF% compared to their actual. Ideal and partner BF% was significantly lower than the perceived BF% for all groups (all p < 0.050). Ideal and partner BF% mean differences (MD) from perceived were positively associated with appearance evaluation (AE) and body area satisfaction (BAS) and negatively associated with overweight preoccupation and self-classified weight for the total sample (all p < 0.050). PerceivedMD demonstrated negative associations with AE and BAS (p < 0.050), but only for females when separated by sex. Perceptual body image measured by DIA is significantly associated with attitudinal body image and may allow practitioners to better quantify this growing issue.

Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model.

Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the accuracy of the artificial intelligence used in DIA is reliant on the accuracy of the developmental methods. Few DIA applications are trained by multicompartment models, but this developmental strategy may be most accurate. Thus, the aim of the present study was to assess the precision and agreement of a DIA application with developmental software trained by a four-compartment (4C) model using an actual 4C model as the criterion method. For this cross-sectional study, body composition estimations were collected from 102 participants (63 females, 39 males) using the methods necessary for a rapid 4C model and a DIA application using two different smartphones. Intraclass correlation coefficients (0.96-0.99; all p < 0.001) and root mean square coefficients of variation (0.5%-3.0%) showed good reliability for body fat percentage, fat mass and fat-free mass. There were no significant mean differences between the 4C model or the DIA estimates for the total sample, by sex, and for non-Hispanic White (n = 61) and Black/African-American (n = 32) participants (all p > 0.050). DIA estimates demonstrated equivalence with the 4C model for all variables but revealed proportional biases that underestimated body fat percentage (both β = -0.25; p < 0.001) and fat mass (both β = -0.07; p < 0.010) at higher degrees of each variable. DIA applications trained by a 4C model are reliable and produce body composition estimates equivalent to an actual 4C model.

Visual and aesthetic markers of gentrification: agency of mapping and tourist destinations

Framed within the context of contemporary place making and the urban tourism destination, a novel trans-disciplinary approach to mapping and interpreting gentrification and cityscape change is presented. A combination of multi-scalar cartographic and visual techniques, including Google Street View (GSV) and geo-tagged images (Photo Sphere), is applied within the setting of Valletta, Malta, to convey cartographically the dynamism of urban transformations and detect tourism-led gentrification in a rapid way through the identification of the visual and aesthetic markers of gentrification. Utilising a critical approach, such map-making can inform and transform the understanding of the processes underpinning urban change and their cartographic and visual representation. It identifies and highlights issues of image and street-level ‘realities’ for both (re)imagining and marketing place. Individual tourists are able to access and utilise GSV and other mobile digital imaging and cartographic tools, as well as social media, to create their own, potentially counter, place-imaginaries and interpretations of urban change, thereby encouraging and/or discouraging visiting the city.

Reduced radiation dose and improved image quality using a mini mobile digital imaging system in a neonatal intensive care unit

This study was aimed to assess the radiation dose and image quality of a mini-mobile digital imaging (mini-DI) system for neonatal chest radiography and compared to conventional digital radiography (DR). A total of 64 neonates were examined and anatomical landmarks were assessed. The entrance surface dose of mini DI and conventional DR was 26.64±0.15 μGy and 49.11±1.46 μGy, respectively (p<0.001). The mean SNR values for mini-DI and DR were 233.2±5.1 and 31.6±1.2, and 10% MTF values were 131 and 161μm. A newly developed mini-DI is capable of preserving the diagnostic information with dose reduction in neonates under intensive care.

The Validity of Mobile Digital Image Plethysmography to Estimate Body Fat in the Middle Aged

The Validity of Mobile Digital Image Plethysmography to Estimate Body Fat in the Middle Aged

Interpretation of Medical Imaging Data with a Mobile Application: A Mobile Digital Imaging Processing Environment

Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users’ expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services.

Grain size variability on a rip-channeled beach

Grain size is an important variable when predicting beach morphodynamics. Beaches, to the eye, seem relatively uniform in grain size and morphodynamic modeling efforts usually assume a single mean grain size for an entire beach environment. Therefore, estimating grain size is traditionally done by collecting only a few samples and averaging to characterize the mean grain size of the whole beach. However, some studies have shown that even small variations in grain size can have a significant effect on model results when predicting beach morphology changes. Here, a mobile digital imaging system (DIS) has been developed for surveying spatial and temporal variation in grain size across a beach following the ideas of Rubin (2004). Using an off-the-shelf camera and underwater housing, macro photographs are taken of sand across a beach, which produce estimates of mean grain size that are highly correlated with estimates from sieves (R 2 = 0.92). High resolution maps of mean surface grain size are produced using the DIS (with ~ 1000 images over a 300 × 500 m area), which suggest that large variations in grain size exist (0.2–0.7 mm over tens of meters with accuracies of ~±0.03 mm) and that there is a correlation between spatial grain size variations and morphological variability.

Automatic image representation and clustering on mobile devices

In this paper a novel approach for the automatic representation of pictures on mobile devices is proposed. With the wide diffusion of mobile digital image acquisition devices, the need for managing a large number of digital images is quickly increasing. In fact, the storage capacity of such devices allow users to store hundreds or even thousands, of pictures that, without a proper organization, become useless. Users may be interested in using (i.e., browsing, saving, printing and so on) a subset of stored data according to some particular picture properties. A content-based description of each picture is needed to perform on-board image indexing. In our work, the images are analyzed and described in three representation spaces, namely, faces, background and time of capture. Faces are automatically detected, and a face representation is produced by projecting the face itself in a common low dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Temporal data is obtained through the extraction of EXIF (Exchangeable Image File Format) data. Faces, background and time information of each image in the collection is automatically organized using a mean-shift clustering technique. Significance of clustering has been evaluated on a realistic set of about 1000 images and results are promising.

The Field Evaluation of a Mobile Digital Image Communication Application Designed for People with Aphasia

PhotoTalk is an application for a mobile device that allows people with aphasia to capture and manage digital photographs to support face-to-face communication. Unlike any other augmentative and alternative communication device for people with aphasia, PhotoTalk focuses solely on image capture and organization and is designed to be used independently. Our project used a streamlined process with three phases: (1) a rapid participatory design and development phase with two speech-language pathologists acting as representative users, (2) an informal usability study with five aphasic participants, which caught usability problems and provided preliminary feedback on the usefulness of PhotoTalk, and (3) a one-month field evaluation with two aphasic participants followed by a one-month secondary field evaluation with one aphasic participant, which showed that they all used it regularly and relatively independently, although not always for its intended communicative purpose. Our field evaluations demonstrated PhotoTalk's promise in terms of its usability and usefulness in everyday communication .