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Seyedshams Feyzabadi

4 accepted papers

2020

Temporal Segmentation of Surgical Sub-tasks through Deep Learning with Multiple Data Sources

ICRA 2020poster

Many tasks in robot-assisted surgeries (RAS) can be represented by finite-state machines (FSMs), where each state represents either an action (such as picking up a needle) or an observation (such as bleeding). A crucial step towards the automation of such surgical tasks is the temporal perception of…

Cited by 53SourceScholar
2020

daVinciNet: Joint Prediction of Motion and Surgical State in Robot-Assisted Surgery

IROS 2020poster

This paper presents a technique to concurrently and jointly predict the future trajectories of surgical instruments and the future state(s) of surgical subtasks in robot-assisted surgeries (RAS) using multiple input sources. Such predictions are a necessary first step towards shared control and supe…

Cited by 37SourceScholar