지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.10
- 수록면
- 951 - 955 (5page)
이용수
초록· 키워드
오류제보하기
Minimally Invasive Surgery (MIS) has become more and more popular in recent years. An endoscopic image tracking system will assist surgeons to adjust the field of view autonomously in MIS. In this paper, we propose a novel image tracking algorithm based on natural features of surgical instruments. We suggest to use texture and geometric features in laparoscopic instrument imagery and to adopt a spiking neural network approach for object detection; considering color will be affected by lighting and the white balance conditions in the endoscope imagery. To enhance tracking performance, we further design a Kalman filter to combine with the neuro-based tracker. The instrument can be detected more robustly despite of deformation of the instrument image during surgery. A laparoscopic video has been tested to verify the developed methods. Experimental results show that two instruments can be distinguished and tracked simultaneously in the surgical video.
목차
Abstract
1. INTRODUCTION
2. PROPOSED TRACKING ALGORITHM
3. INSTRUMENT RECOGNITON UNDER COMPLEX BACKGROUND
4. EXPERIMENT RESULTS
5. CONCLUSION AND FUTURE WORK
REFERENCE
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