The recent information explosion has led to a massively increased demand for multimedia data storage in integrated database systems. Content-based retrieval is an important alternative and complement to traditional keyword-based searching for multimedia data and can greatly enhance information management. However, current content-based image retrieval techniques have some deficiencies when applied in the biomedical functional imaging domain. In this paper, we presented a prototype design for a content-based functional image retrieval database system for dynamic positron emission tomography (PET). The system supports efficient content-based retrieval based on physiological kinetic features and reduces image storage requirements. This design makes it possible to maintain a large number of patient data sets online and to rapidly retrieve dynamic functional image sequences for the interpretation and generation of physiological parametric images, and offers potential advantages in medical image data management and telemedicine, as well as providing possible opportunities in the statistical and comparative analysis of functional image data.

Book reviews - Probalistic models in engineering sciences-- Vol. I, Random variables and stochastic processes--Vol. II, Random noise, signals, and dynamic systems

Content-based retrieval of dynamic PET functional images

We describe the role of various stochastic processes, especially martingales and related concepts, in estimation theory. It is shown, in the simplest context, that in nonlinear estimation theory martingales play the same fundamental role as uncorrelation and white noise do in linear estimation.

Book reviews - Probalistic models in engineering sciences-- Vol. I, Random variables and stochastic processes--Vol. II, Random noise, signals, and dynamic systems

Citations

Content-based retrieval of dynamic PET functional images

References

Stochastic processes in estimation theory

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