Video-based 3D reconstruction, laparoscope localization and deformation recovery for abdominal minimally invasive surgery: a survey
International Journal of Medical Robotics and Computer Assisted Surgery
The intra-operative three-dimensional (3D) structure of tissue organs and laparoscope motion are the basis for many tasks in computerassisted surgery (CAS), such as safe surgical navigation and registration of pre-operative and intra-operative data for soft tissues. Methods This article provides a literature review on laparoscopic videobased intra-operative techniques of 3D surface reconstruction, laparoscope localization and tissue deformation recovery for abdominal minimally invasive surgery
... MIS). Results This article introduces a classification scheme based on the motions of a laparoscope and the motions of tissues. In each category, comprehensive discussion is provided on the evolution of both classic and state-of-the-art methods. Conclusions Video-based approaches have many advantages, such as providing intra-operative information without introducing extra hardware to the current surgical platform. However, an extensive discussion on this important topic is still lacking. This survey paper is therefore beneficial for researchers in this field. The remainder of this article is organized as follows. First, as fundamental tasks in 3D reconstruction and laparoscope localization, feature detection and feature tracking methods are discussed. The discussion is focused on how these detection and tracking methods are designed to overcome the difficulties of MIS images, such as low contrast, specular reflection and smoke. Next, laparoscopic B. Lin et al. Figure 6. MIS-VSLAM methods in rigid and static scenes; solid green curve represents a rigid and static scene B. Lin et al. Rigid/deform, rigid or deforming scene; Batch/sequ, batch or sequential optimization; Framework, type of optimization framework; Mono/stereo, monocular camera or stereo cameras; Feature detection, types of feature detection; Feature matching, types of feature matching; Reg, registration; Sequ., sequential; ASKC, optimization method proposed in (107); Factor, matrix factorization method of rigid SFM; NSSD, normalized SSD. B. Lin et al.