1998
DOI: 10.1118/1.598460
|View full text |Cite
|
Sign up to set email alerts
|

A new genetic algorithm technique in optimization of permanent prostate implants

Abstract: Real time optimized treatment planning at the time of the implant is desirable for ultrasound-guided transperineal 125I permanent prostate implants. Currently available optimization algorithms are too slow to be used in the operating room. The goal of this work is to develop a robust optimization algorithm, which is suitable for such application. Three different genetic algorithms (sGA, sureGA and securGA) were developed and compared in terms of the number of function evaluations and the corresponding fitness.… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
52
0

Year Published

2001
2001
2015
2015

Publication Types

Select...
5
3
1

Relationship

0
9

Authors

Journals

citations
Cited by 77 publications
(52 citation statements)
references
References 23 publications
0
52
0
Order By: Relevance
“…Iteration is performed over all variables until convergence is achieved. Additionally, a genetic algorithm 18 was used to search broad regions of the parameter space. However, we found that the Powell method was quite efficient for finding minima and actually gave superior results.…”
Section: E Powell Minimizationmentioning
confidence: 99%
“…Iteration is performed over all variables until convergence is achieved. Additionally, a genetic algorithm 18 was used to search broad regions of the parameter space. However, we found that the Powell method was quite efficient for finding minima and actually gave superior results.…”
Section: E Powell Minimizationmentioning
confidence: 99%
“…The most common ones are simulated annealing algorithms [14][15][16] and genetic algorithms. [17][18][19] Gradient algorithms also have been applied. 20 In general, gradient algorithms give reproducible solutions but may be trapped in local minima far from the global minimum.…”
Section: Introductionmentioning
confidence: 99%
“…Stochastic approaches are proposed by J. Pouliot [12], Y. Yu [13], [14] and G. Yang [15] et al These approaches are based on either simulated annealing (SA) or genetic algorithm (GA). Deterministic approaches were reported by E. Lee [16], [17] and D'souza et al [18].…”
Section: Introductionmentioning
confidence: 99%