Biomedical subjects

David Dagan Feng

Publications and source records attributed to David Dagan Feng.

4 recordsLinked to original sources

PubMed2005

Performance evaluation of functional medical imaging compression via optimal sampling schedule designs and cluster analysis.

In previous work we have described a technique for the compression of positron emission tomography (PET) image data in the spatial and temporal domains based on optimal sampling schedule designs (OSS) and cluster analysis. It can potentially achieve a high data compression ratio greater than 80:1. However, the number of distinguishable cluster groups in dynamic PET image data is a critical issue for this algorithm that has not been experimentally analyzed on clinical data. In this paper, the problem of experimentally determining the ideal cluster number for the algorithm for PET brain data is addressed.

Algorithms↗

PubMed2005

Introduction to the special issue on advances in clinical and health-care knowledge management.

Clinical and health-care knowledge management (KM) as a discipline has attracted increasing worldwide attention in recent years. The approach encompasses a plethora of interrelated themes including aspects of clinical informatics, clinical governance, artificial intelligence, privacy and security, data mining, genomic mining, information management, and organizational behavior. This paper introduces key manuscripts which detail health-care and clinical KM cases and applications.

Confidentiality↗

PubMed2004

Efficient blind image restoration using discrete periodic radon transform.

Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. Many approaches have been proposed to solve the problem and they have shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data size and long computational time of these approaches are undesirable even with the current computing machines. In this paper, an efficient algorithm is proposed for blind image restoration based on the discrete periodic Radon transform (DPRT). With DPRT, the original two-dimensional blind image restoration problem is converted into one-dimensional ones, which greatly reduces the memory size and computational time required. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.

Algorithms↗

PubMed2002

Dynamic image data compression in the spatial and temporal domains: clinical issues and assessment.

In our previous work, we developed a novel approach to dynamic image data compression, and demonstrated that very high compression ratios can be achieved while preserving relevant kinetic information. However, the technique has not yet been assessed with clinical data. Many issues need to be addressed to tailor the method for clinical use. In this paper, we apply the compression technique to dynamic [18F] 2-fluoro-deoxy-glucose (FDG) brain positron emission tomography (PET) data, using a five-parameter model to include cerebral blood volume (CBV) and partial volume (PV) effects. Functional images generated from the compressed data are compared with those from the original uncompressed data. We show that the storage requirements for a typical clinical dynamic PET image data set can be reduced by more than 95%, without degradation of image quality. Furthermore, the technique greatly reduces the computational complexity of further clinical image postprocessing such as smoothing and generation of functional images. It is expected that the compression technique will be of benefit in image data management and telemedicine.

Algorithms↗