SutureFormer models needle tip movement in video as sequential pixel-space actions via goal-conditioned offline RL with spline-based reward densification, cutting average displacement error by 58.6% on a new 1,158-trajectory kidney suturing dataset.
International Journal of Computer Assisted Radiology and Surgery17(12), 2193–2202 (2022)
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SutureFormer: Learning Surgical Trajectories via Goal-conditioned Offline RL in Pixel Space
SutureFormer models needle tip movement in video as sequential pixel-space actions via goal-conditioned offline RL with spline-based reward densification, cutting average displacement error by 58.6% on a new 1,158-trajectory kidney suturing dataset.