Application of multi-dimensional quality measures to reconstructed medical images

Abstract

Lossy compression drastically reduces the operating costs of digital medical imaging systems by allowing more efficient use of transmission and archival facilities in hospitals and doctors' 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 multi-dimensional measures for image quality. Mimicking the human visual system, they compute local features, and produce a graphical output. Eskicioglu charts, in particular, are shown to be an appropriate tool for characterizing compression losses in reconstructed medical images.<>