[POSTER] Deformation Estimation of Elastic Bodies Using Multiple Silhouette Images for Endoscopic Image Augmentation

Saito, Akira; Nakao, Megumi; Uranishi, Yuki; Matsuda, Tetsuya

doi:10.1109/ismar.2015.49

Cited by 18 publications

(19 citation statements)

References 4 publications

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“…Therefore, the estimation errors are still high. Establishment of a partial displacement observation method using endoscopic image [5] is essential. We consider that acquiring prior knowledge of an elasticity matrix is plausible.…”

Section: Discussionmentioning

confidence: 99%

“…We regard local displacement as a known quantity because deformation measurement methods are often available, such as measurement of surface deformation of elastic bodies using camera images [2][3][4][5] and measurement of inner deformation using ultrasonography [6]. In this study, we assume that the known quantity u o includes the displacement of inner vertices.…”

Section: Formulation Of the Problemmentioning

confidence: 99%

“…This presents a possibility of error or medical malpractice including injury to organs or unexpected rupture of blood vessels from excess force. To remedy this, various intraoperative measurements and physical estimations of the deformed organs [2][3][4][5][6][7] have been attempted. Soft tissues, including organs, are deformed during surgery because of tensile forces exerted by the forceps, the progress of surgery, the state of pneumoperitoneum, and the breath of the patient.…”

Section: Introductionmentioning

confidence: 99%

“…Soft tissues, including organs, are deformed during surgery because of tensile forces exerted by the forceps, the progress of surgery, the state of pneumoperitoneum, and the breath of the patient. Image processing studies such as feature point extraction methods using 3D endoscopes [2][3][4][5] have been attempted to measure the deformation of organs. In addition, ultrasonography is usually used for specifying the location of tumors and is helpful in measuring deformation [6].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of External Forces on the Basis of Local Displacement Observations of an Elastic Body

Sakata

Nakao

Matsuda

2017

ABE

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Surgery can become safer and more reliable if the conditions of the organs can be physically and quantitatively assessed through simultaneous intraoperative measurements and physical estimations of deformed organs. This study proposes a new method for estimating external forces based on local displacement of elastic bodies. Using this method, one can estimate the magnitude and position of forces not only on the forceps but also in the invisible eld. Simulation studies con rmed the effectiveness of this method. The experimental results showed that partial observation of a deformed shape achieved successful estimation of the external forces.

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Section: Discussionmentioning

confidence: 99%

Section: Formulation Of the Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of External Forces on the Basis of Local Displacement Observations of an Elastic Body

Sakata

Nakao

Matsuda

2017

ABE

Self Cite

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“…Plantefeve et al [18] extended this method to the non-rigid alignment using a biomechanical model generated from a preoperative CTscan and anatomical atlas to pre-compute ligaments position. Beside anatomical landmarks, organ silhouette was recently considered by exploiting the organ's rigidity [19], [20] or using multiple views silhouettes [21] or by estimating a 3D contour from the stereo-endoscope.…”

Section: Related Workmentioning

confidence: 99%

Marker-Based Registration for Large Deformations - Application to Open Liver Surgery

Adagolodjo

Golse

Vibert

et al. 2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

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This paper introduces an Augmented Reality (AR) system for open liver surgery. Although open surgery remains the gold-standard for the treatment of complex tumors and central lesions, technological issues actually prevent using AR with sufficient accuracy for clinical use. We propose a markersbased method allowing for the tracking and the deformation of a preoperative model in real-time during the surgery. Markers are manually placed on the surface of the organ after opening the abdominal cavity, and tracked in real-time by a set of infrared cameras. Our framework is composed of both a nonrigid initial registration method, providing an estimation of the location of the markers in the preoperative model, and a realtime tracking algorithm to deform the model during the surgery (even for large deformation or partial occlusion of the organ). The method is validated on both synthetic and ex-vivo samples; in addition, we demonstrate its applicability in the operating room during a liver resection surgery on a human patient. Preliminary studies provided promising results to improve the location of tumors, and to help surgeons into planning the ideal resection intraoperatively.

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Deformable Registration of a Preoperative 3D Liver Volume to a Laparoscopy Image Using Contour and Shading Cues

Koo

Özgür

Roy

et al. 2017

Lecture Notes in Computer Science

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The deformable registration of a preoperative organ volume to an intraoperative laparoscopy image is required to achieve augmented reality in laparoscopy. This is an extremely challenging objective for the liver. This is because the preoperative volume is textureless, and the liver is deformed and only partially visible in the laparoscopy image. We solve this problem by modeling the preoperative volume as a Neo-Hookean elastic model, which we evolve under shading and contour cues. The contour cues combine the organ's silhouette and a few curvilinear anatomical landmarks. The problem is difficult because the shading cue is highly nonconvex and the contour cues give curve-level (and not pointlevel) correspondences. We propose a convergent alternating projections algorithm, which achieves a 4% registration error.

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[POSTER] Deformation Estimation of Elastic Bodies Using Multiple Silhouette Images for Endoscopic Image Augmentation

Cited by 18 publications

References 4 publications

Estimation of External Forces on the Basis of Local Displacement Observations of an Elastic Body

Estimation of External Forces on the Basis of Local Displacement Observations of an Elastic Body

Marker-Based Registration for Large Deformations - Application to Open Liver Surgery

Deformable Registration of a Preoperative 3D Liver Volume to a Laparoscopy Image Using Contour and Shading Cues

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