What question did this study set out to answer?

To develop a keypoint detection network for accurate needle localization during liver interventions using MRI imaging.

April 1, 2026International Journal of Computer Assisted Radiology and Surgery0 citationsOpen Access

Keypoint detection network for needle localization on intra-procedural MRI in MRI-guided liver interventions

WZWenqi ZhouUniversity of California, Los Angeles QDQing DaiUniversity of California, Los Angeles OCOmar CurielUniversity of California, Los Angeles

Puntos clave

To develop a keypoint detection network for accurate needle localization during liver interventions using MRI imaging.
Developed a novel keypoint detection network for needle localization.
Tested the network on single-slice and multislice intra-procedural liver MRI.
Compared performance with traditional segmentation-based models.
Achieved higher accuracy in needle localization compared to segmentation-based methods.
Demonstrated rapid pixel-level localization capabilities.

Resumen

The proposed keypoint detection networks achieved rapid pixel-level needle localization on single-slice and multislice intra-procedural liver MRI with higher accuracy and a more efficient annotation process compared to segmentation-based models.

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Cite This Study

Zhou et al. (Mon,) studied this question.

synapsesocial.com/papers/69ccb6b416edfba7beb885ac https://doi.org/https://doi.org/10.1007/s11548-026-03592-5

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