Random walk-based automated segmentation for the prognosis of malignant pleural mesothelioma
- Resource Type
- Conference
- Authors
- Chen, Mitchell; Helm, Emma; Joshi, Niranjan; Brady, Michael
- Source
- 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. :1978-1981 Mar, 2011
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Robotics and Control Systems
Fires
random walk
image segmentation
non-parametric windows
level sets
mesothelioma
volumetric assessment
RECIST criteria
- Language
- ISSN
- 1945-7928
1945-8452
In this paper we apply the random walk-based segmentation method to mesothelioma CT image datasets, aiming to establish an automatic segmentation routine that can provide volumetric assessments for monitoring progression of the disease and its treatments. We have validated the applicability of this method to our image data through a series of experimental trials, and demonstrated the superior performance and benefits of random walk compared to other segmentation algorithms such as level sets.