Needle insertion planning for obstacle avoidance in robotic biopsy

Abstract Understanding the underlying pathology in different tissues and organs is crucial when fighting pandemics like COVID-19. During conventional autopsy, large tissue sample sets of multiple can be collected from cadavers. However, direct contact with an infectious corpse associated risk disease transmission relatives deceased might object to a autopsy. To overcome these drawbacks, we consider minimally invasive autopsies robotic needle placement as practical alternative. One challenge based biopsies avoidance dense obstacles, including bones or embedded medical devices such pacemakers. We demonstrate approach for automated planning visualising suitable insertion points on computed tomography (CT) scans. Needle paths are modeled by line between target point path occlusion obstacles determined using central projections biopsy surface skin. project maximum minimum CT attenuation, depth, standard deviation attenuation along create two-dimensional intensity-maps projected A cost function considering metrics introduced minimized find optimal path. Furthermore, disregard without sufficient room placement. For visualisation, display color-coded so that become visible. evaluate our system 10 post mortem CTs six targets abdomen thorax annotated experts. all patients found. The mean distance ranges (49.9 ± 12.9)mm spleen (90.1 25.8)mm pancreas.