In vivo evolutionary computation is a novel knowledge-Aided, microrobots-oriented tumor targeting framework, where externally manipulable microrobots are employed to detect the cancer in the human vascular network similar to the procedure of solving an optimization problem by swarm intelligence algorithms. The microrobots play the role of computational agents in the optimization procedure, the vascular network is the search space, and the tumor represents the maximum or minimum to be found by agents. Previous work on this topic provided basic computational models and search strategies, which, however, were solely verified in silico. In this letter, we use Janus microparticles as magnetic microrobots, a two-dimensional microchannel network as the human vasculature, and two representative test functions as the exemplar tumor-Triggered biological gradient fields to validate in vitro the orthokinetic gravitational search algorithm proposed. The results herein demonstrate the advantages of the algorithm by presenting experimental observations on the targeting performance. © 2002-2012 IEEE.
Bibliographical noteThis work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 51850410516, in part by Department of Education of Guangdong Province under Grant 2017KTSCX167, in part by Science and Technology Innovation Committee Foundation of Shenzhen under Grant JCYJ20180302174151692, and in part Shenzhen municipal government Peacock Plan, 20181119590C awarded to U Kei Cheang. The review of this letter was arranged by Associate Editor X. Liu. (Shaolong Shi and Junfeng Xiong contributed equally to this work.)
- cancer detection
- In vivo evolutionary computation
- magnetic microrobot
- microchannel network