Paper Info
Title
Neuro-Radiosurgery Treatments: Mri Brain Tumor Seeded Image Segmentation Based On A Cellular Automata Model
Abstract
Gross Tumor Volume (GTV) segmentation on medical images is an open issue in neuro-radiosurgery. Magnetic Resonance Imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a mini-invasive technique used to deal with inaccessible or insufficiently treated tumors. During the planning phase, the GTV is usually contoured by radiation oncologists using a manual segmentation procedure on MR images. This methodology is certainly time-consuming and operator-dependent. Delineation result repeatability, in terms of both intra-and inter-operator reliability, is only obtained by using computer-assisted approaches. In this paper a novel semi-automatic segmentation method, based on Cellular Automata, is proposed. The developed approach allows for the GTV segmentation and computes the lesion volume to be treated. The method was evaluated on 10 brain cancers, using both area-based and distance-based metrics.
Year
DOI
Venue
2016
10.1007/978-3-319-44365-2_32
CELLULAR AUTOMATA, ACRI 2016
Keywords
Field
DocType
Gamma Knife treatments, MR imaging, Brain tumors, Cellular Automata, Semi-automatic segmentation
Brain cancers,Cellular automaton,Computer science,Segmentation,Brain tumor,Theoretical computer science,Radiosurgery,Image segmentation,Radiation therapy,Artificial intelligence,Radiology,Magnetic resonance imaging
Conference
Volume
ISSN
Citations 
9863
0302-9743
2
PageRank 
References 
Authors
0.40
7
9
Name
Order
Citations
PageRank
Leonardo Rundo1203.55
Carmelo Militello211211.68
Giorgio Russo3113.65
Pietro Pisciotta4100.88
Lucia Maria Valastro520.40
Maria G. Sabini6173.66
Salvatore Vitabile744460.03
Maria Carla Gilardi8589.92
Giancarlo Mauri92106297.38