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Purpose <p>This study aims to address the challenging estimation of trajectories from freehand ultrasound examinations by means of registration of automatically generated surface points. Current approaches to inter-sweep point cloud registration can be improved by incorporating heatmap predictions, but practical challenges such as label-sparsity or only partially overlapping coverage of target structures arise when applying realistic examination conditions.</p> Methods <p>We propose a pipeline comprising three stages: (1) Utilizing a Free Point Transformer for coarse pre-registration, (2) Introducing HeatReg for further refinement using support point clouds, and (3) Employing instance optimization to enhance predicted displacements. Key techniques include expanding point sets with support points derived from prior knowledge and leverage of gradient keypoints. We evaluate our method on a large set of 42 forearm ultrasound sweeps with optical ground-truth tracking and investigate multiple ablations.</p> Results <p>The proposed pipeline effectively registers free-hand intra-patient ultrasound sweeps. Combining Free Point Transformer with support-point enhanced HeatReg outperforms the FPT baseline by a mean directed surface distance of 0.96 mm (40%). Subsequent refinement using Adam instance optimization and DiVRoC further improves registration accuracy and trajectory estimation.</p> Conclusion <p>The proposed techniques enable and improve the application of point cloud registration as a basis for freehand ultrasound reconstruction. Our results demonstrate significant theoretical and practical advantages of heatmap incorporation and multi-stage model predictions.</p>

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3d freehand ultrasound reconstruction by reference-based point cloud registration

  • 期刊论文

  • 发表日期：

    2025年1月7日

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  • Christoph Großbröhmer,
  • Lasse Hansen,
  • Jürgen Lichtenstein,
  • Ludger Tüshaus,
  • Mattias P. Heinrich

摘要

Purpose

This study aims to address the challenging estimation of trajectories from freehand ultrasound examinations by means of registration of automatically generated surface points. Current approaches to inter-sweep point cloud registration can be improved by incorporating heatmap predictions, but practical challenges such as label-sparsity or only partially overlapping coverage of target structures arise when applying realistic examination conditions.

Methods

We propose a pipeline comprising three stages: (1) Utilizing a Free Point Transformer for coarse pre-registration, (2) Introducing HeatReg for further refinement using support point clouds, and (3) Employing instance optimization to enhance predicted displacements. Key techniques include expanding point sets with support points derived from prior knowledge and leverage of gradient keypoints. We evaluate our method on a large set of 42 forearm ultrasound sweeps with optical ground-truth tracking and investigate multiple ablations.

Results

The proposed pipeline effectively registers free-hand intra-patient ultrasound sweeps. Combining Free Point Transformer with support-point enhanced HeatReg outperforms the FPT baseline by a mean directed surface distance of 0.96 mm (40%). Subsequent refinement using Adam instance optimization and DiVRoC further improves registration accuracy and trajectory estimation.

Conclusion

The proposed techniques enable and improve the application of point cloud registration as a basis for freehand ultrasound reconstruction. Our results demonstrate significant theoretical and practical advantages of heatmap incorporation and multi-stage model predictions.