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S Dai

Publications and source records attributed to S Dai.

182 records · Page 11Linked to original sources

A pseudo-Poisson noise model for simulation of positron emission tomographic projection data.

Although radioactive decay obeys Poisson statistics, because of the corrections that are applied to the projection data prior to reconstruction, the noise in positron emission tomography (PET) projections does not follow a Poisson distribution. Use of Poisson noise when simulating PET projections in order to test the performance of reconstruction and processing techniques is therefore not appropriate. The magnitude of PET projection noise was observed to be as much as 10 to 100 times greater than Poisson noise in some instances. A quadratic function was found to fit the relationship between noise power spectral density and total projection count. The coefficients of the quadratic function were determined for projections of different tracer distributions and types. Using these observations, a method of simulating PET projections was developed based on a pseudo-Poisson noise model. Projections simulated according to this method are good approximations to real projection data and take into account the characteristics of individual PET cameras and particular tracer distributions. Such simulated projections have been valuable in predicting the performance of reconstruction algorithms. This approach can also be applied to single photon emission tomography.

Computer Simulation↗

An automated nursing assessment for a teaching hospital.

An automated nursing assessment has been developed by the Department of Nursing and the Center for Clinical Computing at Beth Israel Hospital and Harvard Medical School. Designed to collect standardized data using structured and free-text entry of patient-specific data, the program has been in use on all medical and surgical inpatient units since July 1994. Before it was implemented, each nursing unit had used its own format to document the nursing assessment and there was no standardization of information. The automated system has decreased repetitive entry of data items, improved the legibility and availability of baseline information, increased patient-related communication between nursing units, and reduced the average time spent documenting the admission assessment from 60 to 30 minutes.

Evaluation Studies as Topic↗