Evaluation of High-Efficiency Image Coding algorithm for dermatology images in teledermatology.

ABSTRACT

BACKGROUND: Currently, teledermatology assumes a progressively greater role in the modern healthcare system, especially in consultation, diagnosis, or examining lesions and skin cancers. One of the major challenges facing teledermatology systems is determining the optimal image compression method to efficiently reduce the space needed for electronic storage and data transmission. OBJECTIVE: To the objective and subjective assessment of HEIC compression method on dermatological color images and benchmarking the performance of High-Efficiency Image Coding (HEIC) with different algorithms to a feasibility study of the method for teledermatology. METHODS: Twenty-five clinical and five skin histopathology images were taken in department of dermatology, Imam Reza Hospital, Mashhad, Iran. For each image, a set of 24 compressed images with different compression rates, which is composed of eight JPEG, eight JPEG2000, and eight HEIC images, has been prepared. Compressed and original images were shown simultaneously to three dermatologists and one dermatopathologist with different experiences. Each dermatologist scored quality and suitability of compressed images for diagnostic, as well as educational/scientific purposes. An objective evaluation was performed by calculating the mean "distance" of pixel colors and peak signal-to-noise ratio (PSNR). RESULTS: All compression rates for HEIC were objectively better than JPEG and JPEG2000, particularly at PSNR. Moreover, mean "color distance" per pixel for compressed images using HEIC was lower than others. The subjective image quality assessment also confirms the results of objective evaluation. In both educational and clinical diagnostic applications, HEIC compressed images have the highest score. CONCLUSION: In consideration of objective and subjective evaluation, the HEIC algorithm represents an optimal performance in dermatology images compression compared with JPEG and JPEG2000.