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Locally rigid, vessel-based registration for laparoscopic liver surgery.

Song Y, Totz J, Thompson S, Johnsen S, Barratt D, Schneider C, Gurusamy K, Davidson B, Ourselin S, Hawkes D, Clarkson MJ - Int J Comput Assist Radiol Surg (2015)

Bottom Line: Image guidance provides a potential solution but is challenging in a soft deforming organ such as the liver.We developed a real-time segmentation method to extract vessel centre points from calibrated, freehand, electromagnetically tracked, 2D LUS images.Using landmark-based initial registration and an optional iterative closest point (ICP) point-to-line registration, a vessel centre-line model extracted from preoperative computed tomography (CT) is registered to the ultrasound data during surgery.

View Article: PubMed Central - PubMed

Affiliation: Centre For Medical Image Computing, Engineering Front Building, University College London, Malet Place, London, UK. yi.song@ucl.ac.uk.

ABSTRACT

Purpose: Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet is difficult for most lesions due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but is challenging in a soft deforming organ such as the liver. In this paper, we therefore propose a laparoscopic ultrasound (LUS) image guidance system and study the feasibility of a locally rigid registration for laparoscopic liver surgery.

Methods: We developed a real-time segmentation method to extract vessel centre points from calibrated, freehand, electromagnetically tracked, 2D LUS images. Using landmark-based initial registration and an optional iterative closest point (ICP) point-to-line registration, a vessel centre-line model extracted from preoperative computed tomography (CT) is registered to the ultrasound data during surgery.

Results: Using the locally rigid ICP method, the RMS residual error when registering to a phantom was 0.7 mm, and the mean target registration error (TRE) for two in vivo porcine studies was 3.58 and 2.99 mm, respectively. Using the locally rigid landmark-based registration method gave a mean TRE of 4.23 mm using vessel centre lines derived from CT scans taken with pneumoperitoneum and 6.57 mm without pneumoperitoneum.

Conclusion: In this paper we propose a practical image-guided surgery system based on locally rigid registration of a CT-derived model to vascular structures located with LUS. In a physical phantom and during porcine laparoscopic liver resection, we demonstrate accuracy of target location commensurate with surgical requirements. We conclude that locally rigid registration could be sufficient for practically useful image guidance in the near future.

No MeSH data available.


Related in: MedlinePlus

Evaluation of ultrasound calibration using an eight- point phantom. a Eight-point phantom. b A LUS B-mode scan of pins on phantom. c 3D positions of eight pins obtained from tracked LUS scans are depicted in yellow. The ground truth position of eight pins is depicted in green
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Fig7: Evaluation of ultrasound calibration using an eight- point phantom. a Eight-point phantom. b A LUS B-mode scan of pins on phantom. c 3D positions of eight pins obtained from tracked LUS scans are depicted in yellow. The ground truth position of eight pins is depicted in green

Mentions: The LUS probe was calibrated at a scanning depth of 45 mm before surgery using an invariant point method [17]. The scanning depth of the LUS probe was not changed throughout our experiments. The validation phantom is shown in Fig. 7a, and described further in [4]. Eight pins on the phantom were scanned in turn using the LUS probe. The pin heads were manually segmented from the US images, Fig. 7b. 100 frames were collected at each pin to minimise the impact of manual segmentation error. Their 3D positions in the EM coordinate system were computed by multiplying the 2D pixel location by the calibration transformation and then the EM tracking transformation, Fig. 7c. The accuracy of these computed 3D positions were validated based on two ground truths. The first ground truth is the known geometry of the 8-pin phantom, where the pins are arranged on a grid, with each side being 25 mm in length. The resulting mean edge length was 24.62 mm. The second ground truth is the physical positions of the eight phantom pins in the EM coordinate system, which are measured by using another EM sensor tracked by the same EM transmitter, Fig. 7c. The distance between each reconstructed pin and its ground truth position is listed in Table 1.Fig. 7


Locally rigid, vessel-based registration for laparoscopic liver surgery.

Song Y, Totz J, Thompson S, Johnsen S, Barratt D, Schneider C, Gurusamy K, Davidson B, Ourselin S, Hawkes D, Clarkson MJ - Int J Comput Assist Radiol Surg (2015)

Evaluation of ultrasound calibration using an eight- point phantom. a Eight-point phantom. b A LUS B-mode scan of pins on phantom. c 3D positions of eight pins obtained from tracked LUS scans are depicted in yellow. The ground truth position of eight pins is depicted in green
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4642598&req=5

Fig7: Evaluation of ultrasound calibration using an eight- point phantom. a Eight-point phantom. b A LUS B-mode scan of pins on phantom. c 3D positions of eight pins obtained from tracked LUS scans are depicted in yellow. The ground truth position of eight pins is depicted in green
Mentions: The LUS probe was calibrated at a scanning depth of 45 mm before surgery using an invariant point method [17]. The scanning depth of the LUS probe was not changed throughout our experiments. The validation phantom is shown in Fig. 7a, and described further in [4]. Eight pins on the phantom were scanned in turn using the LUS probe. The pin heads were manually segmented from the US images, Fig. 7b. 100 frames were collected at each pin to minimise the impact of manual segmentation error. Their 3D positions in the EM coordinate system were computed by multiplying the 2D pixel location by the calibration transformation and then the EM tracking transformation, Fig. 7c. The accuracy of these computed 3D positions were validated based on two ground truths. The first ground truth is the known geometry of the 8-pin phantom, where the pins are arranged on a grid, with each side being 25 mm in length. The resulting mean edge length was 24.62 mm. The second ground truth is the physical positions of the eight phantom pins in the EM coordinate system, which are measured by using another EM sensor tracked by the same EM transmitter, Fig. 7c. The distance between each reconstructed pin and its ground truth position is listed in Table 1.Fig. 7

Bottom Line: Image guidance provides a potential solution but is challenging in a soft deforming organ such as the liver.We developed a real-time segmentation method to extract vessel centre points from calibrated, freehand, electromagnetically tracked, 2D LUS images.Using landmark-based initial registration and an optional iterative closest point (ICP) point-to-line registration, a vessel centre-line model extracted from preoperative computed tomography (CT) is registered to the ultrasound data during surgery.

View Article: PubMed Central - PubMed

Affiliation: Centre For Medical Image Computing, Engineering Front Building, University College London, Malet Place, London, UK. yi.song@ucl.ac.uk.

ABSTRACT

Purpose: Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet is difficult for most lesions due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but is challenging in a soft deforming organ such as the liver. In this paper, we therefore propose a laparoscopic ultrasound (LUS) image guidance system and study the feasibility of a locally rigid registration for laparoscopic liver surgery.

Methods: We developed a real-time segmentation method to extract vessel centre points from calibrated, freehand, electromagnetically tracked, 2D LUS images. Using landmark-based initial registration and an optional iterative closest point (ICP) point-to-line registration, a vessel centre-line model extracted from preoperative computed tomography (CT) is registered to the ultrasound data during surgery.

Results: Using the locally rigid ICP method, the RMS residual error when registering to a phantom was 0.7 mm, and the mean target registration error (TRE) for two in vivo porcine studies was 3.58 and 2.99 mm, respectively. Using the locally rigid landmark-based registration method gave a mean TRE of 4.23 mm using vessel centre lines derived from CT scans taken with pneumoperitoneum and 6.57 mm without pneumoperitoneum.

Conclusion: In this paper we propose a practical image-guided surgery system based on locally rigid registration of a CT-derived model to vascular structures located with LUS. In a physical phantom and during porcine laparoscopic liver resection, we demonstrate accuracy of target location commensurate with surgical requirements. We conclude that locally rigid registration could be sufficient for practically useful image guidance in the near future.

No MeSH data available.


Related in: MedlinePlus