Specification Method of Surface Measurement for Surgical Navigation: Ridgeline Based Organ Registration

Furushiro, Naomichi; Saito, Taiga; Masutani, Yoshitaka; Sakuma, Ichiro

doi:10.1007/3-540-45787-9_14

Cited by 5 publications

(6 citation statements)

References 11 publications

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“…Raabe et al 27 illuminated the skin surface with a laser and used optical localization systems to triangulate the depth of the laser spot. Furushiro et al 28 have used range scanners to detect ridgelines in liver phantoms for registration purposes. In other phantom studies, Sinha et al 29 registered range scanner data with texture mapped video information to MR volumes using the simulated cortical surface vessel patterns.…”

Section: Introductionmentioning

confidence: 99%

Incorporation of a laser range scanner into image‐guided liver surgery: Surface acquisition, registration, and tracking

et al. 2003

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As image guided surgical procedures become increasingly diverse, there will be more scenarios where point-based fiducials cannot be accurately localized for registration and rigid body assumptions no longer hold. As a result, procedures will rely more frequently on anatomical surfaces for the basis of image alignment and will require intraoperative geometric data to measure and compensate for tissue deformation in the organ. In this paper we outline methods for which a laser range scanner may be used to accomplish these tasks intraoperatively. A laser range scanner based on the optical principle of triangulation acquires a dense set of three-dimensional point data in a very rapid, noncontact fashion. Phantom studies were performed to test the ability to link range scan data with traditional modes of image-guided surgery data through localization, registration, and tracking in physical space. The experiments demonstrate that the scanner is HHS Public AccessAuthor manuscript Med Phys. Author manuscript; available in PMC 2015 May 27. Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript capable of localizing point-based fiducials to within 0.2 mm and capable of achieving point and surface based registrations with target registration error of less than 2.0 mm. Tracking points in physical space with the range scanning system yields an error of 1.4±0.8 mm. Surface deformation studies were performed with the range scanner in order to determine if this device was capable of acquiring enough information for compensation algorithms. In the surface deformation studies, the range scanner was able to detect changes in surface shape due to deformation comparable to those detected by tomographic image studies. Use of the range scanner has been approved for clinical trials, and an initial intraoperative range scan experiment is presented. In all of these studies, the primary source of error in range scan data is deterministically related to the position and orientation of the surface within the scanner's field of view. However, this systematic error can be corrected, allowing the range scanner to provide a rapid, robust method of acquiring anatomical surfaces intraoperatively.

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Section: Introductionmentioning

confidence: 99%

Incorporation of a laser range scanner into image‐guided liver surgery: Surface acquisition, registration, and tracking

et al. 2003

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“…Other researchers have focused their efforts on phantom studies 25,27 and percutaneous studies, 24,28,[30][31][32] but this work is unique in that it concentrates on acquiring and registering data from open abdominal hepatic tumor resections. Our initial work was also based on phantom studies, which resulted in registration errors of 2.9 mm and targeting errors of 2.8 mm.…”

Section: Discussionmentioning

confidence: 99%

“…Corresponding features between the dataset are identified and aligned by minimizing a distance measure between the two sets of features. [23][24][25][26] The second category uses the complex, feature-rich liver vasculature to drive the registration between preoperative images and intraoperative ultrasound data. [27][28][29] The final type of registration is intensity based, where a correlation measure between two image sets is maximized.…”

Section: Introductionmentioning

confidence: 99%

“…Second, these nonrigid model-based deformation methods will not only improve tumor registration but also the underlying vascular network; that is, the methods will also allow for nonrigid alignment of computerized tomographic angiography, which is of primary importance in resective therapy. Finally, subsurface tumors can confound vascular representation in IOUS; if this method is performed in conjunction with coregistered IOUS, discrepancies in vascular ultrasound images may be corrected.Other researchers have focused their efforts on phantom studies 25,27 and percutaneous studies, 24,28,[30][31][32] but this work is unique in that it concentrates on acquiring and registering data from open abdominal hepatic tumor resections. Our initial work was also based on phantom studies, which resulted in registration errors of 2.9 mm and targeting errors of 2.8 mm.…”

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confidence: 99%

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Concepts and Preliminary Data Toward the Realization of Image-guided Liver Surgery

Cash

Miga

Glasgow³

et al. 2007

Journal of Gastrointestinal Surgery

112

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Image-guided surgery provides navigational assistance to the surgeon by displaying the surgical probe position on a set of preoperative tomograms in real time. In this study, the feasibility of implementing image-guided surgery concepts into liver surgery was examined during eight hepatic resection procedures. Preoperative tomographic image data were acquired and processed. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptAccompanying intraoperative data on liver shape and position were obtained through optically tracked probes and laser range scanning technology. The preoperative and intraoperative representations of the liver surface were aligned using the iterative closest point surface matching algorithm. Surface registrations resulted in mean residual errors from 2 to 6 mm, with errors of target surface regions being below a stated goal of 1 cm. Issues affecting registration accuracy include liver motion due to respiration, the quality of the intraoperative surface data, and intraoperative organ deformation. Respiratory motion was quantified during the procedures as cyclical, primarily along the cranial-caudal direction. The resulting registrations were more robust and accurate when using laser range scanning to rapidly acquire thousands of points on the liver surface and when capturing unique geometric regions on the liver surface, such as the inferior edge. Finally, finite element models recovered much of the observed intraoperative deformation, further decreasing errors in the registration. Image-guided liver surgery has shown the potential to provide surgeons with important navigation aids that could increase the accuracy of targeting lesions and the number of patients eligible for surgical resection. KeywordsImage-guided surgery; Liver resection; Surface registration; Laser range scanning; Finite elementOf the 147,000 projected new cases of colorectal cancer for 2004, 1 it is estimated that 50% of all colorectal primary tumors will develop a liver metastasis at some point in the disease, and 20% of cases will develop a metastasis solely in the liver. 2 Metastatic liver cancer takes a rapid course. When untreated, the median survival rate is between 5 and 12 months with a 5-year survival rate approaching zero. [3][4][5][6] The most common form of treatment is surgical resection. For metastases, studies have reported a 5-year survival rates of 20-50%, with much of the variance attributed to bias in patient selection. For primary liver tumors, the 5-year survival rates varied from 24 to 76% due to variables such as age, size of tumor, and presence of cirrhosis. 2,7-10 With 70-90% of all patients ineligible for resection, ablative techniques provide a promising alternative. [11][12][13][14][15] In the cases of resection and ablation, if the surgeon can direct therapy to the target with an ever higher degree of accuracy, it could lead to smaller resection margins, improved outcomes, and more patients eligible for treatment. To that end, image-guided surgical techniques could...

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“…Thereby 2D ultrasound images are used in clinical routine while all other image sources are applied rarely. An alternative for image acquisition is the laser based scanning of the surface of the liver [11,12]. During the acquisition of intraoperative information the procedure of the intervention has to be interrupted.…”

Section: Introductionmentioning

confidence: 99%

Tracking of the liver for navigation in open surgery

Markert¹,

Koschany²,

Lueth³

2009

Int J CARS

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Specification Method of Surface Measurement for Surgical Navigation: Ridgeline Based Organ Registration

Cited by 5 publications

References 11 publications

Incorporation of a laser range scanner into image‐guided liver surgery: Surface acquisition, registration, and tracking

Incorporation of a laser range scanner into image‐guided liver surgery: Surface acquisition, registration, and tracking

Concepts and Preliminary Data Toward the Realization of Image-guided Liver Surgery

Tracking of the liver for navigation in open surgery

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