Optimising delineation accuracy of tumours in PET for radiotherapy planning using blind deconvolution.

Positron emission tomography (PET) imaging has been proven to be useful in radiotherapy planning for the determination of the metabolically active regions of tumours. Delineation of tumours, however, is a difficult task in part due to high noise levels and the partial volume effects originating mainly from the low camera resolution. The goal of this work is to study the effect of blind deconvolution on tumour volume estimation accuracy for different computer-aided contouring methods. The blind deconvolution estimates the point spread function (PSF) of the imaging system in an iterative manner in a way that the likelihood of the given image being the convolution output is maximised. In this way, the PSF of the imaging system does not need to be known. Data were obtained from a NEMA NU-2 IQ-based phantom with a GE DSTE-16 PET/CT scanner. The artificial tumour diameters were 13, 17, 22, 28 and 37 mm with a target/background ratio of 4:1. The tumours were delineated before and after blind deconvolution. Student's two-tailed paired t-test showed a significant decrease in volume estimation error (p < 0.001) when blind deconvolution was used in conjunction with computer-aided delineation methods. A manual delineation confirmation demonstrated an improvement from 26 to 16 % for the artificial tumour of size 37 mm while an improvement from 57 to 15 % was noted for the small tumour of 13 mm. Therefore, it can be concluded that blind deconvolution of reconstructed PET images may be used to increase tumour delineation accuracy.

A method for reconstructing images from data obtained with a hexagonal bar positron camera.

This paper describes the algorithms and procedures developed for reconstructing images using the hexagonal bar positron camera. This camera has six continuous position-sensitive detectors which are completely stationary, and it has some special software requirements. In particular, spatial nonlinearities in the detectors must be removed in software, the large but sparsely populated data matrix must be reduced in size, and the gaps in the data from the intersections of the detectors must be compensated for. These problems have been investigated, and an appropriate algorithm for this system has been implemented. The effectiveness of this algorithm was evaluated by reconstructing both real and simulated data.

Copy management in a shared care environment using the Internet.

A new approach to sharing medical records using a demand-based database replication method and the Internet e-mail facility is proposed. The underlying model allows subscribed physicians to collect patient records from distant nodes and have local access to these records when needed. A system called the Internet-Based Distributed Medical Information System has been developed and implemented in a shared care environment comprising outpatient clinics, independent practitioners, and diagnostic laboratories. This tool may be highly beneficial in improving coordination among health care professionals and reducing unnecessary repeat investigations.