title: Is JPEG compression of videomicroscopic images compatible with telediagnosis? Comparison between diagnostic performance and pattern recognition on uncompressed TIFF images and JPEG compressed ones.
abstract: Early melanoma diagnosis is an important goal for dermatologists. Polarized light systems are increasingly employed for dermatoscopic diagnosis of melanocytic lesions. For the purpose of teledermoscopy, whose importance is increasingly growing for consultation and teaching purposes, it is of utmost importance to establish whether, after compression, polarized light images maintain their informativeness. The aim of our study was to check the effects of compression on melanocytic lesion images acquired by means of a digital videomicroscope on the identification of morphological details of the image and on diagnostic accuracy. A total of 170 50-fold-magnified pigmented skin lesion images, acquired in Tagged Image File Format (TIFF) by a digital videomicroscope, were compressed using Joint Photographic Experts Group (JPEG) algorithms (compression factor 30). Two experts in videomicroscopy evaluated both original and compressed images twice by describing single lesion features and expressing a diagnosis. Reproducibility in the assessment of dermoscopic parameters and observer performance were studied by kappa statistics and Receiver Operating Characteristic (ROC) analysis. Both intra- and interobserver reproducibility in the assessment of morphological details were higher when TIFF images were considered, indicating a better image quality. Nonetheless, there was no significant difference in the diagnostic accuracy between uncompressed images and compressed ones, although the intraobserver reproducibility in the diagnostic judgement was higher for uncompressed images. Despite loss in image details, factor 30 compressed videomicroscopic images enable a good diagnostic accuracy.
authors.affiliation: Department of Dermatology, University of Modena and Reggio Emilia, Modena, Italy. seidenar@unimo.it
authors.forename: Stefania
authors.initials: S
authors.lastname: Seidenari
authors.forename: Giovanni
authors.initials: G
authors.lastname: Pellacani
authors.forename: Elena
authors.initials: E
authors.lastname: Righi
authors.forename: Anna
authors.initials: A
authors.lastname: Di Nardo
mesh_terms: D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D006801:Humans; D008545:Melanoma / Q000175:diagnosis* / Q000473:pathology*; D018715:Microscopy, Video / Q000295:instrumentation; D015588:Observer Variation; D012878:Skin Neoplasms / Q000175:diagnosis / Q000473:pathology*; D019113:Telepathology / Q000295:instrumentation / Q000379:methods*