Literature DB >> 28241182

Proposed Technical Guidelines for the Acquisition of Clinical Images of Skin-Related Conditions.

Anna Finnane1, Clara Curiel-Lewandrowski2, Glen Wimberley3, Liam Caffery4, Chinmayee Katragadda5, Allan Halpern6, Ashfaq A Marghoob6, Josep Malvehy7, Harald Kittler8, Rainer Hofmann-Wellenhof9, Ivo Abraham10, H Peter Soyer11.   

Abstract

Importance: Standardizing dermatological imaging is important to improve monitoring of skin lesions and skin conditions, ensure the availability of high-quality images for teledermatology, and contribute to the development of a robust archive of skin images to be used for research. Objective: To provide guidelines for the clinical application of the Standards for Dermatological Imaging set forward by the ISIC. Evidence Review: The ISIC recommendations were developed through a hybrid Delphi methodology. The methods for achieving consensus have been described previously. The practical application of these recommendations was evaluated by 2 clinical photographers with expertise in skin imaging. Images corresponding to each recommendation were taken by a clinical photographer and provided as visual examples of how these recommendations can be implemented in clinical practice.
Results: The Standards for Dermatological Imaging developed by the ISIC members could be followed in the clinical setting. Images showing appropriate lighting, background color, field of view, image orientation, focus and depth of field, resolution, and scale and color calibration were obtained by the clinical photographer, by following the detailed recommendations for regional, close-up and dermoscopic images. Conclusions and Relevance: Adhering to the recommendations is both feasible and achievable in practice. Adopting these Standards is the first step in achieving international standardization of skin imaging, with the potential to improve clinical outcomes and research activities.

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Year:  2017        PMID: 28241182     DOI: 10.1001/jamadermatol.2016.6214

Source DB:  PubMed          Journal:  JAMA Dermatol        ISSN: 2168-6068            Impact factor:   10.282


  12 in total

1.  Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.

Authors:  Philipp Tschandl; Noel Codella; Bengü Nisa Akay; Giuseppe Argenziano; Ralph P Braun; Horacio Cabo; David Gutman; Allan Halpern; Brian Helba; Rainer Hofmann-Wellenhof; Aimilios Lallas; Jan Lapins; Caterina Longo; Josep Malvehy; Michael A Marchetti; Ashfaq Marghoob; Scott Menzies; Amanda Oakley; John Paoli; Susana Puig; Christoph Rinner; Cliff Rosendahl; Alon Scope; Christoph Sinz; H Peter Soyer; Luc Thomas; Iris Zalaudek; Harald Kittler
Journal:  Lancet Oncol       Date:  2019-06-12       Impact factor: 41.316

Review 2.  Transforming Dermatologic Imaging for the Digital Era: Metadata and Standards.

Authors:  Liam J Caffery; David Clunie; Clara Curiel-Lewandrowski; Josep Malvehy; H Peter Soyer; Allan C Halpern
Journal:  J Digit Imaging       Date:  2018-08       Impact factor: 4.056

3.  Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

Authors:  Philipp Tschandl; Cliff Rosendahl; Bengu Nisa Akay; Giuseppe Argenziano; Andreas Blum; Ralph P Braun; Horacio Cabo; Jean-Yves Gourhant; Jürgen Kreusch; Aimilios Lallas; Jan Lapins; Ashfaq Marghoob; Scott Menzies; Nina Maria Neuber; John Paoli; Harold S Rabinovitz; Christoph Rinner; Alon Scope; H Peter Soyer; Christoph Sinz; Luc Thomas; Iris Zalaudek; Harald Kittler
Journal:  JAMA Dermatol       Date:  2019-01-01       Impact factor: 10.282

4.  Performance of a deep neural network in teledermatology: a single-centre prospective diagnostic study.

Authors:  C Muñoz-López; C Ramírez-Cornejo; M A Marchetti; S S Han; P Del Barrio-Díaz; A Jaque; P Uribe; D Majerson; M Curi; C Del Puerto; F Reyes-Baraona; R Meza-Romero; J Parra-Cares; P Araneda-Ortega; M Guzmán; R Millán-Apablaza; M Nuñez-Mora; K Liopyris; C Vera-Kellet; C Navarrete-Dechent
Journal:  J Eur Acad Dermatol Venereol       Date:  2020-11-22       Impact factor: 6.166

5.  Multiclass Artificial Intelligence in Dermatology: Progress but Still Room for Improvement.

Authors:  Cristian Navarrete-Dechent; Konstantinos Liopyris; Michael A Marchetti
Journal:  J Invest Dermatol       Date:  2020-10-10       Impact factor: 7.590

6.  Clinical Perspective of 3D Total Body Photography for Early Detection and Screening of Melanoma.

Authors:  Jenna E Rayner; Antonia M Laino; Kaitlin L Nufer; Laura Adams; Anthony P Raphael; Scott W Menzies; H Peter Soyer
Journal:  Front Med (Lausanne)       Date:  2018-05-23

7.  Recent trends in teledermatology and teledermoscopy.

Authors:  Katie J Lee; Anna Finnane; H Peter Soyer
Journal:  Dermatol Pract Concept       Date:  2018-07-31

8.  Automatic Focus Assessment on Dermoscopic Images Acquired with Smartphones.

Authors:  José Alves; Dinis Moreira; Pedro Alves; Luís Rosado; Maria João M Vasconcelos
Journal:  Sensors (Basel)       Date:  2019-11-14       Impact factor: 3.576

Review 9.  Dermoscopy practice guidelines for use in telemedicine.

Authors:  Linda Camaj Deda; Rebecca H Goldberg; Taylor A Jamerson; Ivy Lee; Trilokraj Tejasvi
Journal:  NPJ Digit Med       Date:  2022-04-27

10.  Virtual melanoma checks during a pandemic.

Authors:  M Janda; S M Swetter; C Horsham; H P Soyer
Journal:  Br J Dermatol       Date:  2020-07-13       Impact factor: 11.113

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