Search PubMed⌕ Search

PubMed · 2692549

Stereotactic radiosurgery.

Abstract

Stereotactic radiosurgery is the accurate focusing of ionising radiation onto an intracranial target, and was pioneered in Sweden in the early 1950's. It has proven effective in the treatment of arteriovenous malformations, acoustic tumours and many other small brain lesions. In the last decade the commercial availability of a gamma ray system has led to other centres following the work in Stockholm; more recently, various techniques utilising linear accelerators, (LINACs), have been developed. Both types of system necessitated special dosimetry and treatment planning methods for the small, high dose-gradient circular fields. Localization of the lesions requires angiography, computerised tomography (CT) or magnetic resonance imaging (MRI).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A M Perry, R A Fox. 1989. Stereotactic radiosurgery.. https://pubmed.ncbi.nlm.nih.gov/2692549/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

A penalized likelihood approach to magnetic resonance image reconstruction.

Currently, images acquired via magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) technology are reconstructed using the discrete inverse Fourier transform. While computationally convenient, this approach is not able to filter out noise. This is a serious limitation because the amount of noise in MRI and fMRI can be substantial. In this paper, we propose an alternative approach to reconstruction, based on penalized likelihood methodology. In particular, we focus on non-linear shrinkage estimators and show that this approach achieves a great reduction in integrated mean squared error (IMSE) of the estimated image with respect to the currently used estimator. This approach is extremely fast and easy to implement computationally. In addition, it can be combined with various alternative approaches to MR image reconstruction and can be easily adapted to other, non-MRI contexts, in which the observed data and the quantities of interest are related via a linear transform.

Brain Diseases↗