DocumentCode :
3507842
Title :
Cognitive planning based on Genetic Algorithm in computer-assisted interventions
Author :
Wan Cheng Lim ; Hongliang Ren
Author_Institution :
Dept. of Biomed. Eng., Nat. Univ. of Singapore, Singapore, Singapore
fYear :
2013
fDate :
12-15 Nov. 2013
Firstpage :
190
Lastpage :
194
Abstract :
Minimally invasive and computer-assisted interventions and surgeries are getting widely accepted by patients and clinicians due to improved clinical outcomes. The new paradigm involves more advanced medical instruments, among which Radiofrequency Ablation (RFA) is one type of intervention to kill tumor tissues using a needle-like electrode. In this paper, a computational optimization algorithm to plan optimal ablation delivery is proposed, and potentially allows cognitive planning in surgical robotics. Genetic Algorithm (GA) was used as it can be designed to consider the multi-objective nature of a tumor ablation planning system. A mathematical protocol was also proposed to provide a reference for the viability of the algorithm. The feasibility of GA was tested on simulated and real data; and was found to be able to generate acceptable solution set for the tumor ablation planning problems.
Keywords :
genetic algorithms; medical robotics; path planning; surgery; tumours; GA; RFA; cognitive planning; computational optimization algorithm; computer-assisted interventions; genetic algorithm; mathematical protocol; minimally invasive surgery; multiobjective nature; optimal ablation delivery; radiofrequency ablation; surgical robotics; tumor ablation planning system; Cost function; Genetic algorithms; Planning; Surgery; Trajectory; Tumors; ablation planning; computational interventions; genetic algorithm; multi-objective; optimization; radiofrequency ablation; tumors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics, Automation and Mechatronics (RAM), 2013 6th IEEE Conference on
Conference_Location :
Manila
ISSN :
2158-2181
Print_ISBN :
978-1-4799-1198-1
Type :
conf
DOI :
10.1109/RAM.2013.6758582
Filename :
6758582
Link To Document :
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