Automatic segmentation of organs at risk in head Magnetic Resonance Images (MRI) is a challenging task in medical image analysis. This operation is fundamental for radiotherapy treatment planning: accurate delineation of critical structures allow calibrating the radiation beam in order to hit tumour cells and preserve sane tissues, consuming a time of much lower than a radiation oncologist. In this paper we analyze the properties of head MRI and of their OARs and propose an algorithm that exploits the knowledge implied in an atlas, represented by a labelled medical image, and uses a modified version of Gradient Vector Flow Snake endowed with a parameters automatic tuning mechanism system based on Fourier Descriptors. The comparison of this method with the other traditional algorithms based on active contours showed a remarkable increase of performance.
|Titolo:||Atlas-Based Segmentation of Organs at Risk in Radiotherapy in Head MRIs by Means of a Novel Active Contour Framework|
|Titolo del libro:||Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence|
|Data di pubblicazione:||2010|
|Digital Object Identifier (DOI):||10.1007/978-3-642-14932-0_44|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|