Evaluations of procedures in medical image processing are notoriously difficult and often unconvincing. From a detailed bibliographic study, we analyzed the way evaluation studies are conducted and extracted a number of entities common to any evaluation protocol. From this analysis, we propose here a generic evaluation model (GEM). The GEM includes the notion of hierarchical evaluation, identifies the components which have always to be defined when designing an evaluation protocol and shows the relationships that exist between these components. By suggesting rules applying to the different components of the GEM, we also show how this model can be used as a first step towards guidelines for evaluation.

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As data compression plays now an important role in the development of medical PACS, a technique has been developed for medical image sequences storage and transmission in order to obtain very high compression ratio: in dynamic nuclear medicine studies it can achieve a compression ratio as high as 100:1 without significant degradation. The implemented technique combines two methods which multiply their effects. In a first step, a principal component analysis (PCA) of the image series is performed. It extracts a limited number of principal components and their associated images. For data compression it is not necessary to perform an oblique factor analysis to estimate the so-called 'physiological functions' and their spatial distributions as in factor analysis of dynamic structures (FADS). In a second step, the principal images are compressed by means of a transform coding procedure: an adaptive block-quantization technique using the 2D discrete cosine transform (DCT) is implemented, followed by a statistical quantization method to encode the DCT coefficients. To reconstruct the principal images, an inverse DCT is applied. Then the original series is computed from the reconstructed images combined with the principal components which have been stored without any modification. The reconstructed series is compared to the original series, as well as the time activity curves generated on different regions of interest (ROI) and the factor estimates obtained using FADS performed on the two series. Method and evaluation are illustrated on an example of first pass radionuclide angiocardiography.

This paper deals with the development of standards in the field of medical imaging and picture archiving and communication systems (PACS's), and notably concerning the interworking between PACS's and hospital information systems (HIS). It explains, in detail, how a conceptual model of the management of medical images, such as the medical image management in an open system architecture (MIMOSA) model, can contribute to the development of standards for medical image management and PACS's. This contribution is twofold: 1) Since the model lists and structures the concepts and resources involved to make the images available to the users when and where they are required, and describes the interactions between PACS components and HIS, the MIMOSA work helps by defining a reference architecture which includes an external description of the various components of a PACS, and a logical structure for assembling them. 2) The model and the implementation of a demonstrator based on this model allow the relevance of the Digital Imaging and Communications in Medicine (DICOM) standard with respect to image management issues to be assessed, highlighting some current limitations of this standard and proposing extensions. Such a twofold action is necessary in order both to bring solutions, even partial, in the short term, and to allow for the convergence, in the long term, of the standards developed by independent standardization groups in medical informatics (e.g., those within Technical Committee 251 of CEN: Comité Européen de Normalisation).