Digital Single-lens Reflex Camera Research Articles

A cross-sectional assessment of clinical photography knowledge among dental students in Malaysia.

Dental photography is gaining popularity in contemporary dentistry, but its knowledge was unregulated in most dental schools' curriculum. The study aims to evaluate the level of photography practice and knowledge among dental students in Malaysia, acting as a baseline to include dental photography as a subject in the current curriculum. A series of questions were designed and validated by experts with a content validity index of 0.84. Questionnaires were distributed to the dental students with varied years of clinical experience. The level of knowledge was categorised into poor, weak, subpar, average, good and excellent. The common photography practice and courses attended were also tabulated. Among the 344 respondents, the most commonly used equipment was phone cameras (70.66%), whereas only 16.09% used digital single-lens reflex (DSLR) cameras. The majority of dental students did not attend any photography-related courses (69.48%). Based on the level of photography knowledge, dental students mostly scored 'subpar' (25.84%), with no statistically significant differences between the years of clinical experience (p = 0.236). Therefore, proper and comprehensive dental photography courses should be imparted in the current curriculum to improve students' skills and knowledge.

In Vitro Research Methods Used to Evaluate Shaping Ability of Rotary Endodontic Files-A Literature Review.

In this article, we present a literature review of methods used to measure the shaping ability of endodontic rotary files, including the selection of endodontic sample type (extracted teeth versus simulated blocks) and an imaging evaluation method. This review was conducted as background research to identify concerns that arise when designing research studies in this domain and propose how the field can plan more systematic studies going forward. A literature search was conducted using PubMed, MEDLINE, Embase, ScienceDirect, Scopus, and e B-on databases, including studies published in English from January 2010 to June 2024. Only studies that specified in vitro or ex vivo methods for evaluating the endodontic performance of NiTi rotary files on canal transportation and centering ability were considered. A total of 86 studies met the inclusion criteria from an initial pool of 651. Of these, 67 studies used extracted teeth, while 20 utilized simulated root canals in resin blocks. For evaluation methods, 55 studies employed Micro-Computed Tomography and Cone-Beam Computed Tomography (MCT + CBCT), 30 used Double Digital Images/Radiographs/Photographs (DDIR + DDIP) with software analysis, 1 used both DDIR and MCT, 1 used high-precision nano-CT, and 1 used a digital single-lens reflex (DSLR) camera. The findings indicate that the MCT method and its advanced variations appear superior in many cases for evaluating the quality of root canal instrumentation due to their ability to provide detailed three-dimensional images. We also discuss the pros and cons of other evaluation methods, including CBCT and DDIR. Finally, we identify important factors to consider for optimizing future cross-study comparisons. This work highlights the importance of being familiar with shaping ability assessment methods as new instruments are introduced to the market.

The Assessment of Different Calibration Strategies on the Luminance Measurement Using High Dynamic Range Images

ABSTRACT High Dynamic Range Imaging (HDRI) is an increasingly popular technique for studying the lighting environment through luminance maps. However, a thorough calibration process is necessary to retrieve accurate photometric measurements when generating HDR images using commercially affordable equipment like cameras. This paper aims to provide an overview of the most commonly used luminance calibration strategies and evaluate their effectiveness in luminance measurements. Seven strategies were examined in two experiments consisting of four scenes with varying levels of lighting disparity on the training patches and the testing patches. The LDR images were taken by two professional digital single-lens reflex cameras fitted with the standard zoom lens and merged into HDR images using the software Photomatix. The results indicate the much simpler sRG B D 65 method using a reliable standard target as the reference could deliver a reasonable luminance measurement accuracy which is within 10% even for scenes with large luminance difference on the training and testing patches. Although the more complex camera-specific CTM methods can enhance colorimetric accuracy, they do not significantly improve photometric accuracy. Moreover, it was demonstrated that a linear regression model with an intercept, utilizing pixel luminance extracted from multiple grayscale patches in the HDR image, can serve as a potential solution for checking the significance of the scattering effect and providing a reference for the selection of appropriate reference standards. For lighting researchers seeking an appropriate strategy to calibrate HDR luminance maps, this study can serve as a valuable reference.

Mobilizing International Australian Collections Locally for Global Benefit

From the earliest days of Australian colonization and exploration, botanical collections have been sent to herbaria overseas for western scientific study. Where there is a duplicate set, collections have been repatriated back to Australia with time, but many specimens remain housed overseas. These specimens document the floral diversity of Australian ecoregions that have now been altered, and of species that have not yet been described and may now have been lost to our ecosystems. Many such collections have type specimens, and others have historical exploration and botanical significance, many of which are not readily available for taxonomic and cultural research. One such collection, the Cambridge University Herbarium (CGE), is the fourth largest herbarium in the United Kingdom (Gardiner 2018) and contains more than 13,700 specimens of Australian origin. A collaborative project between the Western Australian Herbarium (PERTH) and CGE, supported by The Winston Churchill Memorial Trust, Australia, has enabled Australian collections to be located, updated, digitized, mobilized, and shared—decolonization and repatriation in digital form. With only five weeks to undertake collection-based activities at CGE, the effort focused on the Australian vascular plant collections. These were systematically located and retrieved from the CGE world collections of flowering plants and ferns (conveniently geographically arranged), and the John Lindley and Charles Fox Bunbury collections, which were only partially incorporated into the world collecitons. Curation was limited to significant repairs and incorporation of loose specimens into the collections. Annotated type specimens were placed within separate folders for easy future identification and curation. Barcodes were adhered to each sheet, and basic metadata was gathered prior to imaging (taxonomic name on the sheet, storage location, type status). Sheets were imaged using two Nikon D850 45.7MP digital single-lens reflex cameras in a lightboxes; image files were converted to 16-bit TIFF for archival storage, full-sized JPGs, and 1MB JPGs for online delivery. With approximately half of the specimens transcribed in September, 2024, preliminary findings include the following: The majority of the Australian collections in CGE are from Western Australia, Tasmania, New South Wales, and South Australia with significantly fewer collections from other Australian states and territories. The majority of specimens were collected in the 1800s and early 1900s, with dominant collectors being James Drummond (collecting in Western Australia), Ronald Gunn (collecting in Tasmania), William Philip Hiern, John Lhotsky, Joseph Jackson Lister, Sir Thomas Livingstone Mitchell, Georgiana Molloy, Fredrick Stimpson Salisbury, and William John Swainson. Prominent individual personal herbarium collections represented included those of Charles Morgan Lemann (1806–1852), John Lindley (1799–1865), John Stevens Henslow (1796–1861) and Charles Edward Moss (1870–1930). Most specimens have little locality information (e.g, "New Holland", "Van Diemen's Land", "Swan River"). More than 475 type specimens have been identified. More than 145 vascular plant families, 875 genera, and ca. 4500 (many non-current) species are housed within the collections (representing approximately 15% of Australian vascular plants). The majority of the Australian collections in CGE are from Western Australia, Tasmania, New South Wales, and South Australia with significantly fewer collections from other Australian states and territories. The majority of specimens were collected in the 1800s and early 1900s, with dominant collectors being James Drummond (collecting in Western Australia), Ronald Gunn (collecting in Tasmania), William Philip Hiern, John Lhotsky, Joseph Jackson Lister, Sir Thomas Livingstone Mitchell, Georgiana Molloy, Fredrick Stimpson Salisbury, and William John Swainson. Prominent individual personal herbarium collections represented included those of Charles Morgan Lemann (1806–1852), John Lindley (1799–1865), John Stevens Henslow (1796–1861) and Charles Edward Moss (1870–1930). Most specimens have little locality information (e.g, "New Holland", "Van Diemen's Land", "Swan River"). More than 475 type specimens have been identified. More than 145 vascular plant families, 875 genera, and ca. 4500 (many non-current) species are housed within the collections (representing approximately 15% of Australian vascular plants). Full transcription of label data (collector, collection date, collection number, locality information, and other collection information) and taxonomic curation is ongoing. Data and high resolution images will be made available soon to the scientific community, historians, and the public for data curation and annotation through the Atlas of Living Australia and other digital platforms. Access to these specimens will be invaluable for botanical research in this age of accelerated biodiversity loss, and as travel to, or shipping of, physical specimens is increasingly fraught and costly.

Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras

The aim of this study was to estimate field-grown tomato yield (weight) and quantity of tomatoes using a self-developed robot and digital single lens reflex (DSLR) camera pictures. The authors suggest a new approach to predicting tomato yield that is based on images taken in the field, 3D scanning, and shape. Field pictures were used for tomato segmentation to determine the ripeness of the crop. A convolution neural network (CNN) model using TensorFlow library was devised for the segmentation of tomato berries along with a small robot, which had a 59.3 % F1 score. To enhance the accurate tomato crop model and to estimate the yield later, point cloud imaging was applied using a Ciclops 3D scanner. The best fitting sphere model was generated using the 3D model. The most optimal model was the 3D model, which gave the best representation and provided the weight of the tomatoes with a relative error of 21.90 % and a standard deviation of 17.9665 %. The results indicate a consistent object-based classification of the tomato crop above the plant/row level with an accuracy of 55.33 %, which is better than in-row sampling (images taken by the robot). By comparing the measured and estimated yield, the average difference for DSLR camera images was more favorable at 3.42 kg.

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%.

Photogrammetry scans for neuroanatomy education-a new multi-camera system: technical note.

Photogrammetry scans has directed attention to the development of advanced camera systems to improve the creation of three-dimensional (3D) models, especially for educational and medical-related purposes. This could be a potential cost-effective method for neuroanatomy education, especially when access to laboratory-based learning is limited. The aim of this study was to describe a new photogrammetry system based on a 5 Digital Single-Lens Reflex (DSLR) cameras setup to optimize accuracy of neuroanatomical 3D models. One formalin-fixed brain and specimen and one dry skull were used for dissections and scanning using the photogrammetry technique. After each dissection, the specimens were placed inside a new MedCreator® scanner (MedReality, Thyng, Chicago, IL) to be scanned with the final 3D model being displayed on SketchFab® (Epic, Cary, NC) and MedReality® platforms. The scanner consisted of 5 cameras arranged vertically facing the specimen, which was positioned on a platform in the center of the scanner. The new multi-camera system contains automated software packages, which allowed for quick rendering and creation of a high-quality 3D models. Following uploading the 3D models to the SketchFab® and MedReality® platforms for display, the models can be freely manipulated in various angles and magnifications in any devices free of charge for users. Therefore, photogrammetry scans with this new multi-camera system have the potential to enhance the accuracy and resolution of the 3D models, along with shortening creation time of the models. This system can serve as an important tool to optimize neuroanatomy education and ultimately, improve patient outcomes.

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.

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.

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.

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.