Abstract

For tumor resections near critical structures, accurate identification of tumor boundaries and maximum removal are the keys to improve surgical outcome and patient survival rate, especially in neurosurgery. In this paper, we propose an intelligent optical diagnosis and treatment system for tumor removal, with automated lesion localization and laser ablation. The proposed system contains a laser ablation module, an optical coherence tomography (OCT) unit, and a robotic arm along with a stereo camera. The robotic arm can move the OCT sample arm and the laser ablation front-end to the suspected lesion area. The corresponding diagnosis and treatment procedures include computer-aided lesion segmentation using OCT, automated ablation planning, and laser control. The ablation process is controlled by a deflectable mirror, and a non-common-path ablation planning algorithm based on the transformation from lesion positions to mirror deflection angles is presented. Phantom and animal experiments are carried out for system verification. The robot could reach the planned position with high precision, which is approximately 1.16mm. Tissue classification with OCT images achieves 91.7% accuracy. The error of OCT-guided automated laser ablation is approximately 0.74mm. Experiments on mouse brain tumors show that the proposed system is capable of clearing lesions efficiently and precisely. We also conducted an ex vivo porcine brain experiment to verify the whole process of the system. An intelligent optical diagnosis and treatment system is proposed for tumor removal. Experimental results show that the proposed system and method are promising for precise and intelligent theranostics. Compared to conventional cancer diagnosis and treatment, the proposed system allows for automated operations monitored in real-time, with higher precision and efficiency.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.