DICODerma: A Practical Approach for Metadata Management of Images in Dermatology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
https://link.springer.com/content/pdf/10.1007/s10278-022-00636-5.pdf
Reference25 articles.
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2. Eapen BR, Archer N, Sartipi K. LesionMap: A Method and Tool for the Semantic Annotation of Dermatological Lesions for Documentation and Machine Learning. JMIR Dermatology. 2020 Apr;3(1):e18149. http://doi.org/10.2196/18149.
3. Caffery LJ, Clunie D, Curiel-Lewandrowski C, Malvehy J, Soyer HP, Halpern AC. Transforming Dermatologic Imaging for the Digital Era: Metadata and Standards. Journal of Digital Imaging. 2018 Aug;31(4):568–577. https://doi.org/10.1007/s10278-017-0045-8.
4. Cao T, Tey HL. High-Definition Optical Coherence Tomography – an Aid to Clinical Practice and Research in Dermatology. JDDG: Journal der Deutschen Dermatologischen Gesellschaft. 2015;13(9):886–890. https://doi.org/10.1111/ddg.12768.
5. Ohshima H, Kinoshita S, Futagawa M, Takiwaki H, Washizaki K, Ishiko A, et al. Quantification of Allergic and Irritant Patch Test Reactions Using ImageJ. Skin Research and Technology. 2014;20(2):177–181. http://doi.org/10.1111/srt.12103.
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