Predicting high‐intensity focused ultrasound thalamotomy lesions using 2D magnetic resonance thermometry and 3D Gaussian modeling

2019 ◽  
Vol 46 (12) ◽  
pp. 5722-5732 ◽  
Author(s):  
Graham M. Seasons ◽  
Erin L. Mazerolle ◽  
Tejas Sankar ◽  
Davide Martino ◽  
Zelma H. T. Kiss ◽  
...  



2013 ◽  
Vol 39 (12) ◽  
pp. 2342-2350 ◽  
Author(s):  
Robert Andrew Fowler ◽  
Sigrid L. Fossheim ◽  
Jean-Louis Mestas ◽  
Jacqueline Ngo ◽  
Emmanuelle Canet-Soulas ◽  
...  




2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
A. Vargas-Olivares ◽  
O. Navarro-Hinojosa ◽  
M. Maqueo-Vicencio ◽  
L. Curiel ◽  
M. Alencastre-Miranda ◽  
...  

High-intensity focused ultrasound (HIFU) is a minimally invasive therapy modality in which ultrasound beams are concentrated at a focal region, producing a rise of temperature and selective ablation within the focal volume and leaving surrounding tissues intact. HIFU has been proposed for the safe ablation of both malignant and benign tissues and as an agent for drug delivery. Magnetic resonance imaging (MRI) has been proposed as guidance and monitoring method for the therapy. The identification of regions of interest is a crucial procedure in HIFU therapy planning. This procedure is performed in the MR images. The purpose of the present research work is to implement a time-efficient and functional segmentation scheme, based on the watershed segmentation algorithm, for the MR images used for the HIFU therapy planning. The achievement of a segmentation process with functional results is feasible, but preliminary image processing steps are required in order to define the markers for the segmentation algorithm. Moreover, the segmentation scheme is applied in parallel to an MR image data set through the use of a thread pool, achieving a near real-time execution and making a contribution to solve the time-consuming problem of the HIFU therapy planning.







Sign in / Sign up

Export Citation Format

Share Document