A 2D-3D Registration Framework for Freehand TRUS-Guided Prostate Biopsy

Khallaghi, Siavash; Sánchez, C. Antonio; Nouranian, Saman; Sojoudi, Samira; Chang, Silvia D.; Abdi, Hamidreza; Machan, Lindsay; Harris, Alison; Black, Peter C.; Gleave, Martin; Goldenberg, Larry; Fels, Sidney; Abolmaesumi, Purang

doi:10.1007/978-3-319-24571-3_33

Cited by 10 publications

(10 citation statements)

References 13 publications

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“…For the 20 registrations, the TRE measured on 3D fiducials was 3.18+/-1.6mm (6.89±4.1 mm before registration). In [8], 115 registrations for 10 volumes and 115 live 2D images were executed based on the trajectory and orientation of the probe from magnetic tracking. Measured on fiducials extracted on 2D and 3D data (about 6 per image), the TRE after non rigid registration was 4.63±1.05 mm (6.31±1.86 mm before registration).…”

Section: Discussionmentioning

confidence: 99%

“…The accuracy we obtained is slightly lower or similar to the one reported in the literature but it must be kept in mind that it corresponds to experiments on a much larger data set obtained from routine recorded data. Also, we com-puted gold standard transforms based on fiducials on 3D volumes, whereas in [8] and [5], the fiducials were identified on 2D slices. Our gold standard transforms computed with 3D fiducials are therefore probably more precise.…”

Section: Discussionmentioning

confidence: 99%

“…Let us stress the fact that in clinics, such inaccurate initialization may happen very often due to prostate or patient uncontrolled motions. In [8], the computation time is about 30 s (resp. 10 min) for rigid and (resp.…”

Section: Discussionmentioning

confidence: 99%

“…Khallaghi et al [8] also proposed a slice-to-volume registration method for freehand prostate biopsies. It includes a trajectory-based rigid registration and a non-rigid model-based registration.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid 2D–3D ultrasound registration for navigated prostate biopsy

2018

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Purpose: We present a hybrid 2D-3D ultrasound (US) rigid registration method for navigated prostate biopsy that enables continuous localization of the biopsy trajectory during the exam.Methods: Current clinical computer-assisted biopsy systems use either sensorbased or image-based approaches. We combine the advantages of both in order to obtain an accurate and real-time navigation based only on an approximate localization of the US probe. Starting with features extracted in both 2D and 3D images, our method introduces a variant of the Iterative Closest Point (ICP) algorithm. Among other differences to ICP, a combination of both the euclidean distance of feature positions and the similarity distance of feature descriptors is used to find matches between 2D and 3D features. The evaluation of the method is twofold. First, an analysis of variance on input parameters is conducted to estimate the sensitivity of our method to their initialization. Secondly, for a selected set of their values, the Target Registration Error (TRE) was calculated on 29,760 (resp. 4,000) registrations in two different experiments. It was obtained using manually identified anatomical fiducials.Results: For 160 US volumes, from 20 patients, recorded during routine biopsy procedures performed in two hospitals by 6 operators, the mean TRE was 3.91±3.22 mm (resp. 4.37±2.62 mm).Conclusion: This work allows envisioning further developments for prostate navigation and their clinical transfer.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid 2D–3D ultrasound registration for navigated prostate biopsy

2018

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“…In 2013, De Silva et al [4] proposed a 2D-3D rigid US registration to compensate for prostate motion with a measured accuracy of less than 2 mm and a speed of 1.1 s. In [8], the same authors improved their method using a prior model of probe-prostate motion. In [9], Khallaghi et al presented a 2D-3D US registration by reconstructing a thin-volume around the real-time 2D US imaging plane. They applied a rigid registration and FEM-based technique for deformation and obtained a mean target registration error (TRE) of 3.15 mm, although not in real-time.…”

Section: Introductionmentioning

confidence: 99%

3D-2D ultrasound feature-based registration for navigated prostate biopsy: A feasibility study

Selmi

Promayon

Troccaz

2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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The aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity-based function. The results are encouraging and show acceptable errors with simulated transforms applied on ultrasound volumes from real patients.

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End-to-end Ultrasound Frame to Volume Registration

Guo

et al. 2021

Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

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A 2D-3D Registration Framework for Freehand TRUS-Guided Prostate Biopsy

Cited by 10 publications

References 13 publications

Hybrid 2D–3D ultrasound registration for navigated prostate biopsy

Hybrid 2D–3D ultrasound registration for navigated prostate biopsy

3D-2D ultrasound feature-based registration for navigated prostate biopsy: A feasibility study

End-to-end Ultrasound Frame to Volume Registration

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