Consistency and Standardization of Color in Medical Imaging: a Consensus Report

This article summarizes the consensus reached at the Summit on Color in Medical Imaging held at the Food and Drug Administration (FDA) on May 8–9, 2013, co-sponsored by the FDA and ICC (International Color Consortium). The purpose of the meeting was to gather information on how color is currently handled by medical imaging systems to identify areas where there is a need for improvement, to define objective requirements, and to facilitate consensus development of best practices. Participants were asked to identify areas of concern and unmet needs. This summary documents the topics that were discussed at the meeting and recommendations that were made by the participants. Key areas identified where improvements in color would provide immediate tangible benefits were those of digital microscopy, telemedicine, medical photography (particularly ophthalmic and dental photography), and display calibration. Work in these and other related areas has been started within several professional groups, including the creation of the ICC Medical Imaging Working Group.

[1]  C Bentley,et al.  Quantitation of vital bleaching by computer analysis of photographic images. , 1999, Journal of the American Dental Association.

[2]  M. Ronnier Luo,et al.  The Fundamentals of Gamut Mapping: A Survey , 2001, Journal of Imaging Science and Technology.

[3]  Wolfgang M Bengel,et al.  Digital photography and the assessment of therapeutic results after bleaching procedures. , 2003, Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.].

[4]  Norimichi Tsumura,et al.  Why Multispectral Imaging In Medicine , 2004 .

[5]  M. Lawrence,et al.  The accuracy of digital-video retinal imaging to screen for diabetic retinopathy: an analysis of two digital-video retinal imaging systems using standard stereoscopic seven-field photography and dilated clinical examination as reference standards. , 2004, Transactions of the American Ophthalmological Society.

[6]  Ehsan Samei,et al.  Assessment of display performance for medical imaging systems: executive summary of AAPM TG18 report. , 2005, Medical physics.

[7]  Charles V. Stewart,et al.  Robust detection and classification of longitudinal changes in color retinal fundus images for monitoring diabetic retinopathy , 2006, IEEE Transactions on Biomedical Engineering.

[8]  Hiroyuki Hashizume,et al.  Video-based telemedicine with reliable color: field experiments of natural vision technology , 2009, IUCS '09.

[9]  Terje Solvoll,et al.  Web‐based consultations for parents of children with atopic dermatitis: results of a randomized controlled trial , 2008, Acta paediatrica.

[10]  I. Ahmad,et al.  Digital dental photography. Part 5: lighting , 2009, BDJ.

[11]  Edward A McLaren,et al.  Combine conventional and digital methods to maximize shade matching. , 2011, Compendium of continuing education in dentistry.

[12]  Hiroyuki Hashizume,et al.  Video-Telemedicine with Reliable Color Based on Multispectral Technology , 2011 .

[13]  Athanasios E Athanasiou,et al.  Sensitivity of digital dental photo CIE L*a*b* analysis compared to spectrophotometer clinical assessments over 6 months. , 2011, American journal of dentistry.

[14]  Yukako Yagi,et al.  Color standardization and optimization in Whole Slide Imaging , 2011, Diagnostic pathology.

[15]  H. Colosi,et al.  A comparison between a new visual method of colour matching by intraoral camera and conventional visual and spectrometric methods. , 2011, Journal of dentistry.

[16]  Louis D. Silverstein,et al.  Observer Performance Using Virtual Pathology Slides: Impact of LCD Color Reproduction Accuracy , 2012, Journal of Digital Imaging.

[17]  Hanna Tiainen,et al.  Clinical color intensity of white spot lesions might be a better predictor of enamel demineralization depth than traditional clinical grading. , 2012, American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics.

[18]  Rafael García,et al.  Computerized analysis of pigmented skin lesions: A review , 2012, Artif. Intell. Medicine.

[19]  Oleg S. Pianykh,et al.  Digital Imaging and Communications in Medicine (DICOM) , 2017, Radiopaedia.org.

[20]  Masahiro Murakawa,et al.  A modified anomaly detection method for capsule endoscopy images using non-linear color conversion and Higher-order Local Auto-Correlation (HLAC) , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[21]  Vasilis Ntziachristos,et al.  Concurrent video-rate color and near-infrared fluorescence laparoscopy , 2013, Journal of biomedical optics.

[22]  John Penczek,et al.  Color Error in the Digital Camera Image Capture Process , 2013, Journal of Digital Imaging.

[23]  L. Zografos,et al.  Pitfalls in colour photography of choroidal tumours , 2013, Eye.

[24]  Marios A. Gavrielides,et al.  Assessing color reproducibility of whole-slide imaging scanners , 2013, Medical Imaging.

[25]  J Martin,et al.  Evaluation of dental restorations: a comparative study between clinical and digital photographic assessments. , 2014, Operative dentistry.