# Markerless Suture Needle 6D Pose Tracking with Robust Uncertainty Estimation for Autonomous Minimally Invasive Robotic Surgery

arXiv: https://arxiv.org/abs/2109.12722 · HTML: https://mlsanity.com/paper/2109.12722/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 34 references that are in the map.
- First posted on arXiv 26 Sep 2021.

## Builds on (most cited first, 7 of 7)

- [Markerless tracking of user-defined features with deep learning](https://mlsanity.com/paper/1804.03142/) (2018)
- [SuPer: A Surgical Perception Framework for Endoscopic Tissue Manipulation with Surgical Robotics](https://mlsanity.com/paper/1909.05405/) (2019)
- [E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception](https://mlsanity.com/paper/2107.00229/) (2021)
- [SuPer Deep: A Surgical Perception Framework for Robotic Tissue Manipulation using Deep Learning for Feature Extraction](https://mlsanity.com/paper/2003.03472/) (2020)
- [Bimanual Regrasping for Suture Needles using Reinforcement Learning for Rapid Motion Planning](https://mlsanity.com/paper/2011.04813/) (2020)
- [Robotic Tool Tracking under Partially Visible Kinematic Chain: A Unified Approach](https://mlsanity.com/paper/2102.06235/) (2021)
- [Automated pick-up of suturing needles for robotic surgical assistance](https://mlsanity.com/paper/1804.03141/) (2018)

## Built on by (most cited first, 5 of 5)

- [Robust Surgical Tool Tracking with Pixel-based Probabilities for Projected Geometric Primitives](https://mlsanity.com/paper/2403.04971/) (2024)
- [Realistic Data Generation for 6D Pose Estimation of Surgical Instruments](https://mlsanity.com/paper/2406.07328/) (2024)
- [Real-Time Constrained 6D Object-Pose Tracking of An In-Hand Suture Needle for Minimally Invasive Robotic Surgery](https://mlsanity.com/paper/2210.11973/) (2022)
- [SurgIRL: Towards Life-Long Learning for Surgical Automation by Incremental Reinforcement Learning](https://mlsanity.com/paper/2409.15651/) (2024)
- [PICO: Projection-Informed Consistency Optimisation for 6DoF Surgical Tool Pose Estimation](https://mlsanity.com/paper/2609.30989/) (2026)

## Abstract (arXiv)

Suture needle localization is necessary for autonomous suturing. Previous approaches in autonomous suturing often relied on fiducial markers rather than markerless detection schemes for localizing a suture needle due to the inconsistency of markerless detections. However, fiducial markers are not practical for real-world applications and can often be occluded from environmental factors in surgery (e.g., blood). Therefore in this work, we present a robust tracking approach for estimating the 6D pose of a suture needle when using inconsistent detections. We define observation models based on suture needles' geometry that captures the uncertainty of the detections and fuse them temporally in a probabilistic fashion. In our experiments, we compare different permutations of the observation models in the suture needle localization task to show their effectiveness. Our proposed method outperforms previous approaches in localizing a suture needle. We also demonstrate the proposed tracking method in an autonomous suture needle regrasping task and ex vivo environments.