Dermatological diagnostic accuracy by conventional photography: A prelude to digital image interpretation and telemedicine

1997 ◽  
Vol 3 (1_suppl) ◽  
pp. 105-105 ◽  
Author(s):  
P V Harrison ◽  
Martin Patefield ◽  
Y Dickenson ◽  
Rhiannon Morgan
Keyword(s):  
Diagnostic Accuracy ◽  
Digital Image ◽  
Image Interpretation

scholarly journals Comparison of wide field imaging by nurses with indirect ophthalmoscopy by ophthalmologists for retinopathy of prematurity: a diagnostic accuracy study

BMJ Open ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. e036483
Author(s):  
Sam Ebenezer Athikarisamy ◽  
Geoffrey Christopher Lam ◽  
Stuart Ross ◽  
Shripada Cuddapah Rao ◽  
Debbie Chiffings ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Retinopathy Of Prematurity ◽  
Roc Curve ◽  
Image Interpretation ◽  
Wide Field ◽  
Index Test ◽  
Diagnostic Accuracy Study ◽  
Neonatal Nurses ◽  
Indirect Ophthalmoscopy ◽  
Accuracy Study

ObjectivesRetinopathy of prematurity (ROP) is a vasoproliferative disease of the preterm retina with the potential to cause irreversible blindness. Timely screening and treatment of ROP are critical. Neonatal nurses trained in wide field digital retinal photography (WFDRP) for screening may provide a safe and effective strategy to reduce the burden of ophthalmologists in performing binocular indirect ophthalmoscopy (BIO). The objective of the study was to determine the diagnostic accuracy of WFDRP in the diagnosis of referral warranting ROP (RWROP).DesignProspective diagnostic accuracy study.SettingA tertiary neonatal intensive care unit in Perth, Western Australia.ParticipantsPreterm infants who fulfilled the Australian ROP screening criteria (gestational age (GA) <31 weeks, birth weight (BW) <1250 g).InterventionSets of 5–6 images per eye (index test) were obtained within 24–48 hours prior to or after the BIO (reference standard), and uploaded onto a secured server. A wide field digital camera (RetCam, Natus, Pleasanton, California, USA) was used for imaging. A paediatric ophthalmologist performed the BIO. The ophthalmologists performing BIO versus reporting the images were masked to each other’s findings.Primary outcomeThe area under the receiver operating characteristic (ROC) curve was used as a measure of accuracy of WFDRP to diagnose RWROP.ResultsA total of 85 infants (mean BW; 973.43 g, mean GA; 29 weeks) underwent a median of two sessions of WFDRP. There were 188 episodes of screening with an average of five images per eye. WFDRP identified RWROP in 7.4% (14/188 sessions) of examinations. In one infant, BIO showed bilateral plus disease and WFDRP did not pick up the plus disease. WFDRP image interpretation had a sensitivity of 80%, specificity of 94.5% for the detection of RWROP. The ‘area under the ROC curve’ was 88% when adjusted for covariates.ConclusionsWFDRP by neonatal nurses was feasible and effective for diagnosing RWROP in our set up.Trial registration numberACTRN12616001386426.

scholarly journals A Comparison of the Diagnostic Accuracy of in-situ and Digital Image-Based Assessments of Coral Health and Disease

2020 ◽  
Vol 7 ◽  
Author(s):  
John H. R. Burns ◽  
Grady Weyenberg ◽  
Travis Mandel ◽  
Sofia B. Ferreira ◽  
Drew Gotshalk ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Digital Image ◽  
Health And Disease ◽  
Coral Health

scholarly journals Pupil diameter changes reflect difficulty and diagnostic accuracy during medical image interpretation

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Tad T. Brunyé ◽  
Marianna D. Eddy ◽  
Ezgi Mercan ◽  
Kimberly H. Allison ◽  
Donald L. Weaver ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Medical Image ◽  
Pupil Diameter ◽  
Image Interpretation

scholarly journals Differentiating Experience From Cue Utilization in Radiological Assessments

2020 ◽  
pp. 001872082090257 ◽  
Author(s):  
Ann J. Carrigan ◽  
John Magnussen ◽  
Andrew Georgiou ◽  
Kim M. Curby ◽  
Thomas J. Palmeri ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Assessment Tool ◽  
Image Interpretation ◽  
Training Needs ◽  
Years Of Experience ◽  
Cue Utilization ◽  
Domain Specific

Objective This research was designed to examine the contribution of self-reported experience and cue utilization to diagnostic accuracy in the context of radiology. Background Within radiology, it is unclear how task-related experience contributes to the acquisition of associations between features with events in memory, or cues, and how they contribute to diagnostic performance. Method Data were collected from 18 trainees and 41 radiologists. The participants completed a radiology edition of the established cue utilization assessment tool EXPERTise 2.0, which provides a measure of cue utilization based on performance on a number of domain-specific tasks. The participants also completed a separate image interpretation task as an independent measure of diagnostic performance. Results Consistent with previous research, a k-means cluster analysis using the data from EXPERTise 2.0 delineated two groups, the pattern of centroids of which reflected higher and lower cue utilization. Controlling for years of experience, participants with higher cue utilization were more accurate on the image interpretation task compared to participants who demonstrated relatively lower cue utilization ( p = .01). Conclusion This study provides support for the role of cue utilization in assessments of radiology images among qualified radiologists. Importantly, it also demonstrates that cue utilization and self-reported years of experience as a radiologist make independent contributions to performance on the radiological diagnostic task. Application Task-related experience, including training, needs to be structured to ensure that learners have the opportunity to acquire feature–event relationships and internalize these associations in the form of cues in memory.

scholarly journals Expertise development in volumetric image interpretation of radiology residents: what do longitudinal scroll data reveal?

2020 ◽  
Author(s):  
Dorien van Montfort ◽  
Ellen Kok ◽  
Koen Vincken ◽  
Marieke van der Schaaf ◽  
Anouk van der Gijp ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Residency Training ◽  
Image Interpretation ◽  
Expertise Development ◽  
Image Perception ◽  
Holistic Model ◽  
Process Measures ◽  
Information Reduction ◽  
Radiology Residency ◽  
Radiology Residents

Abstract The current study used theories on expertise development (the holistic model of image perception and the information reduction hypothesis) as a starting point to identify and explore potentially relevant process measures to monitor and evaluate expertise development in radiology residency training. It is the first to examine expertise development in volumetric image interpretation (i.e., CT scans) within radiology residents using scroll data collected longitudinally over five years of residency training. Consistent with the holistic model of image perception, the percentage of time spent on full runs, i.e. scrolling through more than 50% of the CT-scan slices (global search), decreased within residents over residency training years. Furthermore, the percentage of time spent on question-relevant areas in the CT scans increased within residents over residency training years, consistent with the information reduction hypothesis. Second, we examined if scroll patterns can predict diagnostic accuracy. The percentage of time spent on full runs and the percentage of time spent on question-relevant areas did not predict diagnostic accuracy. Thus, although scroll patterns over training years are consistent with visual expertise theories, they could not be used as predictors of diagnostic accuracy in the current study. Therefore, the relation between scroll patterns and performance needs to be further examined, before process measures can be used to monitor and evaluate expertise development in radiology residency training.

scholarly journals Validation of a Novel Cutaneous Neoplasm Diagnostic Self-Efficacy Instrument (CNDSEI) for Evaluating User-Perceived Confidence With Dermoscopy

2020 ◽  
pp. e2020088
Author(s):  
Kelly C. Nelson ◽  
Ashley E. Brown ◽  
Amanda Herrmann ◽  
Chloe Dorsey ◽  
Julie M. Simon ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Diagnostic Accuracy ◽  
Self Efficacy ◽  
Medical Image ◽  
Image Interpretation ◽  
Primary Care Providers ◽  
Care Providers ◽  
Internal Reliability ◽  
Medical Specialties ◽  
Dermoscopic Image

Background: Accurate medical image interpretation is an essential proficiency for multiple medical specialties, including dermatologists and primary care providers. A dermatoscope, a ×10-×20 magnifying lens paired with a light source, enables enhanced visualization of skin cancer structures beyond standard visual inspection. Skilled interpretation of dermoscopic images improves diagnostic accuracy for skin cancer. Objectives: Design and validation of Cutaneous Neoplasm Diagnostic Self-Efficacy Instrument (CNDSEI)—a new tool to assess dermatology residents’ confidence in dermoscopic diagnosis of skin tumors. Methods: In the 2018-2019 academic year, the authors administered the CNDSEI and the Long Dermoscopy Assessment (LDA), to measure dermoscopic image interpretation accuracy, to residents in 9 dermatology residency programs prior to dermoscopy educational intervention exposure. The authors conducted CNDSEI item analysis with inspection of response distribution histograms, assessed internal reliability using Cronbach’s coefficient alpha (α) and construct validity by comparing baseline CNDSEI and LDA results for corresponding lesions with one-way analysis of variance (ANOVA). Results: At baseline, residents respectively demonstrated significantly higher and lower CNDSEI scores for correctly and incorrectly diagnosed lesions on the LDA (P = 0.001). The internal consistency reliability of CNDSEI responses for the majority (13/15) of the lesion types was excellent (α ≥ 0.9) or good (0.8≥ α <0.9). Conclusions: The CNDSEI pilot established that the tool reliably measures user dermoscopic image interpretation confidence and that self-efficacy correlates with diagnostic accuracy. Precise alignment of medical image diagnostic performance and the self-efficacy instrument content offers opportunity for construct validation of novel medical image interpretation self-efficacy instruments.

scholarly journals Pemanfaatan Citra Landsat 8 untuk Identifikasi Sebaran Vegetasi di Kecamatan Pangandaran

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ridwan Saidi ◽  
Nisvi Nur’adqiah ◽  
Yusifa Muzri ◽  
Lu’lu’ Izzatul Fawziah ◽  
Reza Pahlawan ◽  
...  
Keyword(s):  
Digital Image ◽  
Field Data ◽  
Vegetation Index ◽  
Image Interpretation ◽  
Residential Area ◽  
Digital Data ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Accurate Analysis ◽  
Accuracy Test

This study aims to determine: (1) the density of vegetation in Pangandaran district. (2)the result of comparison of vegetation density from digital image interpretation using the NDVI transformation with the results of validation. This research was done in pangandaran regency, which is located at coordinates 108º 41 - 1090 East Longitude and 07o 41-07 07 50 South Latitude has an area of up to 61 km². This research was conducted in several stages, namely: (1) the preparation of tools and data, (2) digital data processing, (3) field data collection, and (4) data analysis. Thanks to the density of vegetation can be done quickly by way of digital image interpretation using NDVI (Normalized Difference Vegetation Index) transformation. The purpose of this research is to know the land arrangement in Pangandaran District and for vegetation index of residential area in Pangandaran District. The object of this research is residential area in Pangandaran District. The data used are Landsat Image 8 year 2018. The software used is ENVI 5.1 and ArcGIS 10.3 software. The method used is the classification of land use and the calculation of NDVI in ENVI which then classified based on the range of NDVI index values. The results showed that the density of vegetation in Pangandaran District was dominating  classified and as quite dense but it needed a lot of updating of its digital image and data so that the accuracy rate increased between imagery and field data. Vegetation in Pangandaran Subdistrict is mostly dominated by teak, waru, coconut, Chinese petai, goat, santigi, and ketapang. Based on the results of the interpretation accuracy test, obtained an accuracy value for the entire sample of 57% so that the results of image interpretation and field checks regarding vegetation density cannot be accepted because the expected level of interpretation accuracy is 85%, while the accuracy test results get a value of 57%. To get a complete picture of the availability of green open space in Pangandaram Regency, fast and relatively more accurate analysis of high spatial resolution is needed. The satellite imagery used in this study is Landsat 8 Imagery which has never been used in previous studies. Analysis of these images uses a vegetation index / NDVI that can directly distinguish plants from non-plants. The results of this image analysis also produce digital data that can be processed quantitatively for further research purposes.

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