This paper considers the semi-automated robotic medical procedure for removing the mind tumor margins where in fact the manual operation is a tedious and time-consuming task for surgeons. aided neurosurgery where in fact the difficulty and high level of sensitivity from the anatomical areas requires fine accuracy and dexterity [1] [2]. With this research we consider the robotic automation of the medical subtask in mind tumor ablation medical procedures i.e. removal of cancerous margin under surgeon’s guidance. A. Clinical Situation Full resection of the mind tumors can be a extremely essential element for patient’s success rate and existence quality. A retrospective research greater than 400 individuals with glioblastoma demonstrated significantly longer success times for individuals with resection of 98 % or even more from the tumor quantity than for all those with a smaller degree of resection [3]. In the suggested medical scenario the assumption is a medical cavity with feasible cancerous materials on its wall structure will be subjected after manual removal of the majority mind tumor by cosmetic surgeon. The suggested medical task can be clean-up from the tumor margins in the medical cavity. The present day biomarker-’Tumor color’ [4] that selectively binds towards gamma-secretase modulator 3 the tumor cells and fluoresces with lighting from the conjugated dye will be employed for discovering the tumor margins under a fluorescence-based imaging program utilizing a 1.6mm size gamma-secretase modulator 3 Scanning Dietary fiber Endoscope (SFE) [5]. The cancerous areas could be segmented in the wide-field fluorescence picture that’s co-registered with color reflectance SFE picture. Because of the fragile fluorescence reactions and lengthy integration period for picture collection manual treatment of the tagged tumor SSH1 tissue can be tedious and needs high precision slicing over long length. Thus this surgical procedure becomes a perfect applicant for the computerized robotic job. B. Preliminary gamma-secretase modulator 3 Research 1 Three-dimensional digital reconstruction of the medical cavity Gong et al. [6] demonstrated the feasibility from the 3D picture reconstruction of the medical cavity utilizing a group of 2D pictures extracted from SFE (Shape 1). Fig. 1 The 3D reconstruction of the spherical tumor cavity phantom with medical residual and image fluorescence tumor focuses on. (a). A 3d imprinted phantom with consistency of mind surgery picture glued on its surface area. (b) Picture sampling grid 5×6 above phantom. … 2 Behavior Tree platform for autonomous robotic surgical procedure The potential energy of Behavior Tree (BT) like a modeling vocabulary for smart robotic surgical treatments was explored in [7]. A BT representation from the semi-automated mind tumor ablation was proven for simplified planar geometry and software program integration was applied. C. Technical Element This paper is made upon the above mentioned preliminary function and discusses an intermediate stage towards the prepared intelligent robotic medical system that may scan the cavity for fluorescently tagged tissue subjected by mass tumor gamma-secretase modulator 3 removal and instantly treat that materials. This procedure will be repeated until no cancerous tissue is available. Especially with this paper a path is presented simply by us planner because of this surgical procedure. Provided the tumor segmentation map produced from 3D picture reconstruction our planner will synthesize pathways which totally cover the segmented region at the mercy of medical constraints: Full removal of most labeled cells. Minimize removing gamma-secretase modulator 3 normal cells. The tumor margin can be assumed to become homeomorphic to a sphere (that’s have no openings) but will probably have tendrils that may require specialized programs. A surgeon will need to have dependable control and pick the trusted arrange for robotic treatment. The acquired 3D segmentation map can be represented like a point-cloud which can be relatively soft on the top because of the installing algorithm in reconstruction nevertheless may differ in geometrical size and shape. To cope with the geometrical irregularity our suggested complete coverage route planner provides various kinds of paths predicated on the evaluation of decoration. Three main types of route pattern are found in preparation: zig-zag contour-parallel and a combined design of both based on geometry evaluation. Combined with the generated route plans the road planner also computes the amount of device retractions (when multiple pathways of an idea are located) the full total amount of via-points aswell as around execution time of every plan..