Digital Single-lens Reflex Camera Research Articles

Low-cost, high-volume imaging for entomological digitization.

Large-scale digitization of natural history collections requires automation of image acquisition and processing. Reflecting this fact, various approaches, some highly sophisticated, have been developed to support imaging of museum specimens. However, most of these systems are complex and expensive, restricting their deployment. Here we describe a simple, inexpensive technique for imaging arthropods larger than 5 mm. By mounting a digital SLR camera on a CNC (computer numerical control) motor-drive rig, we created a system that captures high-resolution z-axis stacked images (6960 × 4640 pixels) of 95 specimens in 30 minutes. This system can be assembled inexpensively ($1000 USD without a camera) and it is easy to set-up and maintain. By coupling low cost with high production capacity, it represents a solution for digitizing any natural history collection.

Digital Fracture Porosity Measurement using Digital Outcrop Modelling (DOM)

Abstract Fracture measurements for porosity calculations often experience problems such as barely accessible locations, limited area coverage, and a long time to carry out field data measurements. Therefore, refined alternative methods are necessary to obtain the most favourable data. This study demonstrates fracture measurements through application of Digital Outcrop Modelling (DOM) using the Structure from Motion (SfM) method to utilize digital photogrammetry techniques. This method was chosen because data collection can be done remotely using Light Detection and Ranging (LiDAR) or digital photogrammetry to obtain point cloud data that is used to perform three-dimensional outcrop modeling. In addition, SfM also produces high-resolution data without the need for experts, is cost-efficient and safer than other methods. Hand-held platform Canon 700D digital single lens reflex (DSLR) camera was used in this study to capture data from an area of a square meter located on the riverbed that requires detailed modeling. DOM using SfM is applied to conduct aperture measurements in fractures inside the scan window, later used as data for calculating basement fracture porosity predictions. Field data collection is also carried out to validate data generated by DOM. Calculations achieved from field data and DOM data will be compared to determine differences of the porosity prediction values. Field data collection was carried out on 3 scan windows, each one is an area of 1 m2 and in totals obtained 117 fracture data, consist of 44 extension joints, 34 release joints, 7 shear joints, and 32 non-systematic joints. In this study, 115 photos were taken from scanwindow 1, 162 photos from scanwindow 2, and 158 photos from scanwindow 3 to construct the DOM using agisoft metashape software. The difference in these values can be used as a correction formula or evaluation for further research. The results of measuring basement fracture porosity using data generated by DOM will remain in the range of less than 1%.

Assessment of Image Quality and Child Acceptance for DSLR, Bridge and Smartphone Cameras Used in Dental Photography (A Comparative Study)

Digital photography is of huge importance during the course of dental treatments. It’s indispensable for recording data, patient motivation, communication with the lab etc. Many photography equipment are available and used in dentistry. Using digital photography is obtaining a footstep in pediatric dentistry. The purpose of this study is to evaluate the quality of dental images made by different digital photography mediums commonly used in dental clinics and measure the acceptance of children towards dental photography. Materials and Methods: in this study images produced by Three DSLR (digital single lens reflex) cameras along their prober lenses, one bridge camera and two smartphones with different sensor sizes were evaluated, based upon the sharpness, quality, color fidelity, and general context of the photographs. The participants were divided into three main groups: under-graduate students; graduated dentists and graduated dentists with photography experience. 20 pediatric patients were imaged using the aforementioned equipment. Results: DSLRs with macro lenses and ring flashes scored the highest means with statistically significant differences (p<0.05). From 20 pediatric patient photographed by each equipment used in this study 18 child accepted smartphone photography Conclusion: Older DSLRS are still usable for dental photography. Kit lenses or extension tubes with camera built in flashes are not appropriate for dental photography. Bridge cameras and smartphones are not adequate for dental photography.

Is there a difference in quality of photographs obtained using smartphones, compared to the photographs obtained via digital single-lens reflex camera?

PurposeThe purpose of this study was to compare the quality of photographs obtained with three different cameras: I-phone, Samsung, and DSLR, as assessed by Oral and Maxillofacial Surgeons (OMSs). MethodsThis was an anonymous online survey study. The study population consisted of OMSs in New Jersey, New York, Pennsylvania, and Massachusetts who were members of their state societies. Primary outcome variable was ratings on the quality of extraoral and intraoral photographs obtained with three different cameras. Predictor variable was type of camera used to obtain the photographs: I-Phone, Samsung, and DSLR camera. Descriptive statistics were computed. Spearman test was utilized to analyze correlation between the outcome variables. ResultsMajority of respondents were from full time private practice (n = 84, 77.06%), followed by full time academia (n = 12, 11.01%). Spearman test revealed negligible correlation between extraoral and intraoral photographs on the best quality rating (0.15, p=0.13). Negligible correlation between extraoral and intraoral photographs were noted on the second best (0.15, p=0.11), and least quality rating (0.09, p=0.32). ConclusionStudy results revealed that there is no difference between the quality of photographs obtained using smartphones, compared to the photographs obtained via DSLR camera. Future discussions on an ideal application on smartphones would allow for consent and transfer of high-quality photographs via a secure messaging system between healthcare providers to address ethical concerns of confidentiality.

Automatic detection of color markings and numbers on trees in point clouds from Personal Laser Scanning (PLS) and Terrestrial Laser Scanning (TLS)

In forestry, colored spray paint is used for different purposes, such as marking trees that are chosen for the next harvest or that will be promoted by future silvicultural activities, or for the demarcation of skid/cable roads. Numerous studies have demonstrated the application of Terrestrial Laser Scanners (TLS) and Personal Laser Scanners (PLS) for the acquisition of tree parameters (diameters, heights, and tree positions) in a forest inventory context. However, no studies have included classification based on spectral information by applying colored markings to trees. When a laser scanner is combined with a camera, the color information can be mapped onto the laser point cloud, allowing for additional analysis of spectral information. In this study, we have tested the analysis of joint information from imagery and 3D point clouds in two different settings: (i) PLS point cloud data from a GeoSLAM ZEB Horizon were complemented with spectral information from images collected with a NCTech iSTAR Pulsar 360-degree camera, (ii) TLS point cloud data from a RIEGL VZ-400i were combined with imagery from a Nikon D850 digital single lens reflex (DSLR) camera with 14 mm fisheye lens. The major objective was to automatically classify trees that were marked with colored sprays automatically identify the numbers sprayed on the trees. The marked trees could be classified correctly with a balanced accuracy of 77.26% for PLS and 98.01% for the data collected with the TLS system using a support vector machine (SVM) model. The numbers written on the trees were classified from the TLS data using a YOLOv8 model. The accuracy of the digit classification reached up to 97.30%. In conclusion, it is possible to automatically detect marked trees and to automatically recognize the numbers spayed on these trees from colored point cloud data. However, accuracy strongly depends on the selected combination of scanner and camera. The findings of future research on this subject might differ with the ongoing development of PLS systems and could be enhanced by creating a large dataset of handwritten numbers collected using laser scanning systems.

Versatile luminescence thermometry via intense green defect emission from an infrared-pumped fluorosilicate optical fiber

An all-glass optical fiber capable of two distinct methods of optical thermometry is described. Specifically, a silica-clad, barium fluorosilicate glass core fiber, when pumped in the infrared, exhibits visibly intense green defect luminescence whose intensity and upper-state lifetime are strong functions of temperature. Intensity-based optical thermometry over the range from 25°C to 130°C is demonstrated, while a lifetime-based temperature sensitivity is shown from 25°C to 100°C. Time-domain measurements yield a relative sensitivity of 2.85%K−1 at 373 K (100°C). A proof-of-concept distributed sensor system using a commercial digital single-lens reflex camera is presented, resulting in a measured maximum relative sensitivity of 1.13%K−1 at 368 K (95°C). The sensing system described herein stands as a new blueprint for defect-based luminescence thermometry that takes advantage of pre-existing and relatively inexpensive optical components, and allows for the use of standard cameras or simply direct human observation.

A Preliminary Evaluation of the Diagnostic Performance of a Smartphone-Based Machine Learning-Assisted System for Evaluation of Clinical Activity Score in Digital Images of Thyroid-Associated Orbitopathy.

Background: We previously developed a machine learning (ML)-assisted system for predicting the clinical activity score (CAS) in thyroid-associated orbitopathy (TAO) using digital facial images taken by a digital single-lens reflex camera in a studio setting. In this study, we aimed to apply this system to smartphones and detect active TAO (CAS ≥3) using facial images captured by smartphone cameras. We evaluated the performance of our system on various smartphone models and compared it with the performance of ophthalmologists with varying clinical experience. Methods: We applied the preexisting ML architecture to classify photos taken with smartphones (Galaxy S21 Ultra, iPhone 12 pro, iPhone 11, iPhone SE 2020, Galaxy M20, and Galaxy A21S). The performance was evaluated with smartphone-captured images from 100 patients with TAO. Three ophthalmology residents, three general ophthalmologists with <5 years of clinical experience, and three oculoplastic specialists independently interpreted the same set of images taken under a studio environment and compared their results with those generated by the smartphone-based ML-assisted system. Reference CAS was determined by a consensus of three oculoplastic specialists. Results: Active TAO (CAS ≥3) was identified in 28 patients. Smartphone model used in capturing facial images influenced active TAO detection performance (F1 score 0.59-0.72). The smartphone-based system showed 74.5% sensitivity, 84.8% specificity, and F1 score 0.70 on top three smartphones. On images from all six smartphones, average sensitivity, specificity, and F1 score were 71.4%, 81.6%, and 0.66, respectively. Ophthalmology residents' values were 69.1%, 55.1%, and 0.46. General ophthalmologists' values were 61.9%, 79.6%, and 0.55. Oculoplastic specialists' values were 73.8%, 90.7%, and 0.75. This smartphone-based ML-assisted system predicted CAS within 1 point of reference CAS in 90.7% using facial images from smartphones. Conclusions: Our smartphone-based ML-assisted system shows reasonable accuracy in detecting active TAO, comparable with oculoplastic specialists and outperforming residents and general ophthalmologists. It may enable reliable self-monitoring for disease activity, but confirmatory research is needed for clinical application.

Recognition performance of different artificial neural networks for distinguishing banana slices subjected to different combinations of pretreatment and microwave drying

This study was aimed at assessing the effect of microwave drying at 100, 200, or 300 W on the quality of Cavendish banana slices without pretreatment and with pretreatment using 5% ascorbic acid solution, 5% citric acid solution, 5% gum arabic solution, and ultrasound. Banana slices were imaged using a digital single-lens reflex (SLR) camera. The acquired images were processed to extract texture parameters. The classification models were developed based on image texture parameters selected from a big dataset of 2172 textures of images in different color channels using artificial neural networks. Wide Neural Network, Bilayered Neural Network, Medium Neural Network and three classifiers from the group of function, such as RBF (Radial basis function) Network, Multilayer Perceptron, and WiSARD were applied. Banana slices belonging to 15 classes with different combinations of pretreatment and microwave drying were distinguished with an average accuracy of up to 97.2% for a model built using Multilayer Perceptron. For most models, banana samples microwave-dried at 200 W without pretreatment were classified with the highest correctness. The performed study revealed that the objective, non-destructive, correct, and robust quality assessment of pretreated and microwave-dried banana slices may be performed using image processing and artificial intelligence.

Photogrammetry: Adding Another Dimension to Virtual Gross Pathology Teaching

Pathology is a discipline that relies on the description and interpretation of changes occurring in organs and tissues, and it is largely a “hands-on” experience, both during training and professional practice. Instigated by the need to provide a solution for online learning and teaching, a plethora of different approaches have been tested during the Covid-19 pandemic. The enforced inability to meet in person created the necessity to quickly replace the hands-on experience of practical classes, routinely considered the “gold standard” in undergraduate pathology teaching, with alternative and innovative digital solutions that could allow the students to appreciate most, if not all, features of the specimen to describe and interpret. Here we present a successful deployment of photogrammetry for the purpose of teaching gross veterinary pathology to undergraduate students. Fresh specimens obtained during routine diagnostic post-mortem activity have been photographed using Digital Single-Lens Reflex cameras and rendered into high quality 3D models, preserving almost unaltered morphology, color, and texture, when compared to the original specimen. Once processed using photogrammetry software, exported and uploaded into an online repository, 3D models become readily available via our digital learning platform (CANVAS) to all undergraduate students for self-study and consolidation, as well as to teaching staff for use during online lectures, traditional face-to-face classes, small group teaching and seminars. Preliminary data collected from students’ feedback highlighted the positive reception from users, and the enriched learning experience, while prolonging indefinitely the availability of rare and perishable teaching material.

Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain

RAW to sRGB mapping, which aims to convert RAW images from smartphones into RGB form equivalent to that of Digital Single-Lens Reflex (DSLR) cameras, has become an important area of research. However, current methods often ignore the difference between cell phone RAW images and DSLR camera RGB images, a difference that goes beyond the color matrix and extends to spatial structure due to resolution variations. Recent methods directly rebuild color mapping and spatial structure via shared deep representation, limiting optimal performance. Inspired by Image Signal Processing (ISP) pipeline, which distinguishes image restoration and enhancement, we present a novel Neural ISP framework, named FourierISP. This approach breaks the image down into style and structure within the frequency domain, allowing for independent optimization. FourierISP is comprised of three subnetworks: Phase Enhance Subnet for structural refinement, Amplitude Refine Subnet for color learning, and Color Adaptation Subnet for blending them in a smooth manner. This approach sharpens both color and structure, and extensive evaluations across varied datasets confirm that our approach realizes state-of-the-art results. Code will be available at https://github.com/alexhe101/FourierISP.

Accreditation of the handheld 3-dimensional scanner and conventional photo images for area measurement.

Accurate assessment of wound areas is crucial in making therapeutic decisions, as the prognosis and changes in the size of the wound over time play a significant role. An ideal assessment method should possess qualities such as speed, affordability, accuracy, user-friendliness for both patients and healthcare professionals, and suitability for daily clinical practice. This study aims to introduce a handheld 3-dimensional (3D) scanner and evaluate its accuracy in measuring wound areas. Engineers from the Industrial Technology Research Institute in Taiwan developed a handheld 3D scanner with the intention of extending its application to the medical field. A project was conducted to validate the accuracy of this 3D scanner. We utilized a smartphone (Asus ZenFone 2 with a 13-million-pixel rear camera), a digital single-lens reflex digital camera (Nikon, D5000, Tokyo, Japan), and the 3D scanner to repeatedly measure square papers of known size that were affixed to the curved surface of life-size facial mask or medical teaching breast models. The "Image J" software was employed for 2-dimensional image measurements, while the "3D Edit" software was used to assess the "area of interest" on 3D objects. By using square papers with predetermined dimensions, the measurement-associated error rate (ER) could be calculated for each image. Three repeated measurements were performed using the "Image J" software for each square paper. The ERs of the 3D scan images were all below 3%, with an average ER of 1.64% in this study. The close-up mode of the smartphone exhibited the highest ER. It was observed that as the area increased, the ER also increased in the digital single-lens reflex camera group. The extension distortion effect caused by the wide-angle lens on the smartphone may increase the ER. However, the definition of a healthy skin edge may vary, and different algorithms for calculating the measurement area are employed in various 3D measurement software. Therefore, further validation of their accuracy for medical purposes is necessary. Effective communication with software engineers and discussions on meeting clinical requirements are crucial steps in enhancing the functionality of the 3D scanner.

Intermittent cryogen spray cooling coupled with cold air jet for heat transfer enhancement and cryogen saving of laser dermatology

Laser dermatology has become a convenient technique for medical treatment. However, the epidermal temperature could be increased, leading to intolerable side effects. Cryogen spray cooling (CSC) is implemented to decrease epidermal damage, but the current CSC could increase cryogen wastage. In this study, the CSC is coupled with a cold air jet (CAJ) and is further subjected to intermittent strategy (ICSC) to mitigate film deposition, enhance heat transfer, and save cryogen consumption, through CAJ-to-spray interaction. The surface temperature is measured by a thin film type-T thermocouple, while the heat transfer is estimated by enhanced Duhamel theorem. The film intensity is captured by a digital single-lens reflex camera through the scattering-illumination technique. The results affirmed the benefits of using ICSC/ICSC-CAJ for laser dermatology. It demonstrated lower surface temperature, film intensity, and film resistance as well as higher convection and efficiency compared with CSC. ICSC-CAJ showed the lowest minimum temperature (1.8%–4.9% decrement) and film resistance (3.8%–17.5% decrement), the highest average convective coefficient (84%–92% increment) and efficiency (7%–9% increment) compared with ICSC. Lower frequency and moderate duties would be preferable for ICSC, while higher frequency and lower duties would be preferable for ICSC-CAJ. The efficiency increased with the saving (110% increment), which insights into our understanding of alternative enhancement toward cryogen saving strategy.

Utility of intraoral scanner imaging for dental plaque detection.

Oral hygiene, maintained through plaque control, helps prevent periodontal disease and dental caries. This study was conducted to examine the accuracy of plaque detection with an intraoral scanner (IOS) compared to images captured with an optical camera. To examine the effect of color tone, artificial tooth resin samples were stained red, blue, and green, after which images were acquired with a digital single-lens reflex (DSLR) camera and an IOS device. Stained surface ratios were then determined and compared. Additionally, the deviation rate of the IOS relative to the DSLR camera was computed for each color. In the clinical study, following plaque staining with red disclosing solution, the staining was captured by the DSLR and IOS devices, and the stained area on each image was measured. The stained surface ratios did not differ significantly between DSLR and IOS images for any color group. Additionally, the deviation rate did not vary significantly across colors. In the clinical test, the stained plaque appeared slightly lighter in color, and the delineation of the stained areas less distinct, on the IOS compared to the DSLR images. However, the stained surface ratio was significantly higher in the IOS than in the DSLR group. When employing IOS with dental plaque staining, the impact of color was minimal, suggesting that the traditional red stain remains suitable for plaque detection. IOS images appeared relatively blurred and enlarged relative to the true state of the teeth, due to inferior sharpness compared to camera images.

Angular Photogrammetric Analysis for a Young Adult Garhwali Population

Abstract Objectives: The aim of this study is to quantify the average parameters that define the soft-tissue facial profile of a young adult Garhwali population of age 18–21 by means of angular measurement on standardized photographs. Materials and Methods: A sample of 50 Garhwali individuals (25 males and 25 females) between 18 and 21 years of age was obtained with a class I dental relationship. The photographic set-up consisted of a tripod that held a digital SLR camera. The photographic records of the subjects were taken in natural head posture. The obtained records were digitized and analyzed using the Digimizer software program. Twelve measurements were digitally analyzed on each photograph. For statistical evaluation, Student’s-t-test was performed and reliability of the method was analyzed. The results were compared with established soft-tissue profile photogrammetric norms. Results: The Student’s t-test was applied to all variables to determine the influence of sex in the measurements. Two of the angles showed sexual differences: nasofrontal (G–N–Prn, P = 0.001) and mentolabial angle (Li–Sm–Pg, P = 0.002). Nasofrontal angle was found wider in the females while mentolabial angle was found be wider in the males. Conclusion: Orthodontist has the ability to alter facial features and must analyze the soft-tissue facial profile and compare it with standard measurements of the soft- tissue facial profile. The sample’s mean values can be compared against records of participants using the same photogrammetric technique and sharing the same attributes. The results showed sexual differences in two of the measurements: the nasofrontal and mentolabial angle.

Accuracy, acceptability and feasibility of photography for use in trachoma surveys: a mixed methods study in Tanzania.

Photography could be used to train individuals to diagnose trachomatous inflammation-follicular (TF) as trachoma prevalence decreases and to ensure accurate field TF grading in trachoma prevalence surveys. We compared photograph and field TF grading and determined the acceptability and feasibility of eyelid photography to community members and trachoma survey trainers. A total of 100 children ages 1-9y were examined for TF in two Maasai villages in Tanzania. Two images of the right everted superior tarsal conjunctiva of each child were taken with a smartphone and a digital single-lens reflex (DSLR) camera. Two graders independently graded all photos. Focus group discussions (FGDs) were conducted with community members and Tropical Data trainers. Of 391 photos, one-fifth were discarded as ungradable. Compared with field grading, photo grading consistently underdiagnosed TF. Compared with field grading, DSLR photo grading resulted in a higher prevalence and sensitivity than smartphone photo grading. FGDs indicated that communities and trainers found photography acceptable and preferred smartphones to DSLR in terms of practicalities, but image quality was of paramount importance for trainers. Photography is acceptable and feasible, but further work is needed to ensure high-quality images that enable accurate and consistent grading before being routinely implemented in trachoma surveys.

An In Vitro Comparative Assessment of Shaping Capacity of a Single-File System Over Multiple-File System in Root Canals.

The study's objective was to contrast the two distinct rotary file techniques used to shape mandibular first molars. The investigation involved twenty recently removed mandibular molars. A digital single-lens reflex (DSLR) camera was placed in a fixed position, a muffle block was built, and images of each tooth's three cross sections were obtained. The specimens were split into the following two groups at random: Rotary files from WaveOne were used to prepare group A and Mtwo rotary files were used to prepare group B. At the coronal, middle, and apical thirds of the root canals, WaveOne file system demonstrated improved centering ability compared with the Mtwo file system (P 0.05). When compared to the Mtwo file system, WaveOne file system demonstrated improved centering capabilities and needed significantly less time to build the curved canals.

REMOTE MONITORING OF RADIATION TEST TEMPERATURE REGIME AT A HIGH-CURRENT ELECTRON ACCELERATOR

Methods for evaluating the radiation resistance of structural materials of nuclear reactors have been developed and research is being carried out in NSC KIPT. As a part of these studies, a supercritical water convection loop with a chamber for irradiation of the tested samples by electron beam of the accelerator LU-10 (beam energy of 8…10 MeV, beam power up to 10 kW) was developed. A pyrometric system based on a DSLR camera (Digital Single-Lens Reflex Camera) has been created for the remote continuous non-intrusive control of the surface temperature of the irradiation cell in the range of 350…550°С. The work presents the results of calibration and use of the developed system in the conditions of a 500-hour run of sample irradiation in the loop.

Comparing image quality and trachoma detection across three camera types from a survey in Kongwa, Tanzania.

There is an increasing demand for photography for trachoma prevalence surveys. In previous studies, digital single lens reflex (DSLR) images were superior to smartphone images, but newer-model smartphones and/or lens attachments may be able to bridge this gap. This study compares the image quality and ability to detect trachomatous inflammation - follicular (TF) of three camera types: a DSLR Nikon camera, an iPhone SE and an iPhone 13 Pro with a cell scope. We surveyed 62 children ages 1-7y from two Tanzanian communities. Upper tarsal conjunctiva images of both eyes were graded for TF by two standardized graders. The McNemar's test and a logistic regression model were used for analyses. The DSLR camera malfunctioned during the study, thus the iPhone SE and iPhone 13 Pro with cell scope were both more likely to take high-quality, gradable photographs (88% and 86%, respectively) compared with the DSLR camera (69%) (p<0.001 and p=0.02, respectively). TF was detected in gradable images from the iPhone SE (8.8%) and iPhone 13 Pro with cell scope (9.0%) at the same rate (p=1.0) as images from the DSLR camera (9.7%). Smartphones with high-quality image capture, like the iPhone SE/13 Pro, have the potential for use in trachoma surveys if the proportion of gradable images can be improved.

Agreement in quantification of removable prosthesis plaque area coverage using a semi-automated planimetric assessment method

ObjectivesTo determine the agreement of removable dental prosthesis cleanliness as assessed by a semi-automated planimetric method between images captured by a digital single-lens reflex camera (DSLR) and smartphone. MethodsA total of 97 participants with removable prostheses were recruited for the quantification of the prosthesis plaque area coverage. The colour images of stained prosthesis plaque were obtained using both a DSLR camera and a smartphone. The prosthesis plaque area coverage was analysed in two ways: (i) prosthesis cleanliness index (PCI) and (ii) percentage plaque area coverage (PPC). The PPC (continuous data) was converted to the PCI (categorical data) to provide prevalence ordinal scales and the agreements in PCI ratings were determined using weighted Kappa statistics. Agreement of PPC scores was determined through assessing directional, standardised directional, and absolute differences and correlation analyses. ResultsWeighted Kappa values of agreement between PCI categories were excellent (> 0.80) for all comparisons. The mean PPC was 24.79 % as determined by DSLR and 25.37 % as determined by smartphone. There was no statistically significant difference in the means of PPC between the DSLR and smartphone (P = 0.149). The standardised directional difference was 0.15 (‘small’). The mean absolute difference was 2.77. The interclass correlation coefficient was 0.98 (‘excellent’). ConclusionsThis method showed almost perfect agreements and allowed for threshold-based plaque segmentation on the removable prostheses. There was substantial agreement between DSLR and smartphone assessment of prosthesis plaque area coverage as determined by a semi-automated planimetric assessment. Clinical significanceThis semi-automated planimetric assessment method has implications for monitoring removable prosthesis hygiene initiatives by offering a valid, reliable, and quantitative method of assessment with potential use in managed care and community settings.

Quantifying Facial Distortion in Modern Digital Photography.

Advancements in digital cameras and the advent of smartphones have magnified the importance of clinical photography in facial plastic surgery. Here, we aim to examine the effect of different camera types, focal lengths, and distances from subjects on facial distortion. Twelve subjects underwent a series of frontal photographs using a smartphone camera and a full-frame digital single-lens reflex camera. Photos were captured at six distances from the subject. Seven focal lengths were used at each distance for the full-frame camera. Measurements of facial landmarks were made for each photo, with those made at 60 inches using the full-frame camera considered the gold standard and used for comparison. Distortion of facial features using the full-frame camera occurred when photos were captured 8 inches away using short focal lengths. A 12%-19% increase in vertical stretching of the midface occurred when using focal lengths of 24, 35, and 50 mm (p < 0.05 for all). The same features were distorted when a smartphone camera was used at 8 inches (18% increase, p < 0.01) and 12 inches (12% increase, p < 0.03). Distortion of midfacial features using both smartphones and full-frame cameras occurs with short, 'selfie' distances between the camera and subject. 2 Laryngoscope, 134:1234-1238, 2024.