Application of multidimensional quality measures to reconstructed medical images

Lossy compression drastically reduces the operating costs of digital medical imaging systems by enabling more efficient use of transmission and archival facilities in hospitals and doctor's offices. To be able to develop standards for the application of this technology, reliable tools are needed for measuring the quality of reconstructed images. Among the most common measures presently used, the normalized mean squared error (NMSE) does not provide any information concerning the type of impairment, and receiver operating characteristic (ROC) analyses are expensive and time-consuming. This paper evaluates the performance of three quantitative multidimensional measures for image quality. Mimicking the human visual system, they compute local features, and produce a graphical output. Improved Eskicioglu charts, in particular, are shown to be appropriate tools for characterizing compression losses in reconstructed medical images. (C) 1996 Society of Photo-Optical Instrumentation Engineers.