Title :
Hausdorff Distance based 3D Quantification of Brain Tumor Evolution from MRI Images
Author :
Nicolier, F.M. ; Lebonvallet, S. ; Baudrier, E. ; Su Ruan
Author_Institution :
CRESTIC-URCA, Troyes
Abstract :
This paper presents a quantification method which can be used to quantify the evolution of a brain tumor with time. From two segmented volumes, a local distance volume (LDV) based on Hausdorff distance is computed to show the true physical local distances between them. In the case of tracking a tumor volume during a therapeutic treatment, local variations can thus be shown by the LDV in particular where the tumor has regressed and where it has growed. This information can help radiologists to adapt the current treatment.
Keywords :
biomedical MRI; brain; distance measurement; image segmentation; medical image processing; tumours; 3D brain tumor evolution quantification; Hausdorff distance; LDV; MRI images; local distance volume; tumor volume tracking; Biomedical imaging; Distortion measurement; High definition video; Image analysis; Image segmentation; Magnetic resonance imaging; Medical diagnostic imaging; Neoplasms; Robustness; Volume measurement; Algorithms; Artificial Intelligence; Brain Neoplasms; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Neoplasm Invasiveness; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353615
