Consistency and standardization of color in medical imaging: a consensus report

Abstract

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.

Fig. 1

Observed variation in color between scanners and software. a, b The same slide imaged with the same scanner, viewed using two different software packages (screenshots). c The same slide imaged on two different scanners with IHC (top) and H&E (bottom) stains. The color rendition of the scans appears noticeably different from scanner A to B

Fig. 2

Left panel observed variability in the color obtained by imaging the same patient on four different fundus cameras from three different manufacturers. Right panel fundus images obtained by applying color camera profiles after capture

Fig. 3

Color patches a captured in each fundus camera inside a model eye and b image-processed to match original targets

Fig. 4

Dermoscopy picture of a malignant melanoma of the skin. The characteristic blue-white veil has high diagnostic value but requires precise color rendering to be identifiable (image courtesy of Dr. Herbert Kirchesch)

Fig. 5

End-to-end calibrated visualization of the color information along the imaging chain

Fig. 6

Example image data to be used to diagnose possible skin disease for the same patient and different hardware (image courtesy of Dr. Herbert Kirchesch)

Fig. 7

Observed color variation from RGB and six-band multispectral surgery image