2016
Patient-Specific Biomechanical Modeling for Guidance During Minimally-Invasive Hepatic Surgery
PLANTEFÈVE, Rosalie; Igor PETERLÍK; Nazim HAOUCHINE and Stéphane COTINBasic information
Original name
Patient-Specific Biomechanical Modeling for Guidance During Minimally-Invasive Hepatic Surgery
Name in Czech
Biomechanické Modelování pro Navigaci Speficickou pro Pacienta během minimimálně invasivní hepatické chirurgie
Authors
PLANTEFÈVE, Rosalie (250 France); Igor PETERLÍK (703 Slovakia, belonging to the institution); Nazim HAOUCHINE (12 Algeria) and Stéphane COTIN (250 France)
Edition
ANNALS OF BIOMEDICAL ENGINEERING, NEW YORK, SPRINGER, 2016, 0090-6964
Other information
Language
English
Type of outcome
Article in a journal
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Germany
Confidentiality degree
is not subject to a state or trade secret
References:
Impact factor
Impact factor: 3.221
RIV identification code
RIV/00216224:14610/16:00089426
Organization unit
Institute of Computer Science
UT WoS
000367330800012
EID Scopus
2-s2.0-84952871290
Keywords in English
Patient-specific modeling; Non-rigid registration; Minimally-invasive surgery; Real-time simulation
Tags
Tags
International impact, Reviewed
Changed: 27/4/2018 10:06, Mgr. Alena Mokrá
Abstract
In the original language
During the minimally-invasive liver surgery, only the partial surface view of the liver is usually provided to the surgeon via the laparoscopic camera. Therefore, it is necessary to estimate the actual position of the internal structures such as tumors and vessels from the pre-operative images. Nevertheless, such task can be highly challenging since during the intervention, the abdominal organs undergo important deformations due to the pneumoperitoneum, respiratory and cardiac motion and the interaction with the surgical tools. Therefore, a reliable automatic system for intra-operative guidance requires fast and reliable registration of the pre- and intra-operative data. In this paper we present a complete pipeline for the registration of pre-operative patient-specific image data to the sparse and incomplete intra-operative data. While the intra-operative data is represented by a point cloud extracted from the stereo-endoscopic images, the pre-operative data is used to reconstruct a biomechanical model which is necessary for accurate estimation of the position of the internal structures, considering the actual deformations. This model takes into account the patient-specific liver anatomy composed of parenchyma, vascularization and capsule, and is enriched with anatomical boundary conditions transferred from an atlas. The registration process employs the iterative closest point technique together with a penalty-based method. We perform a quantitative assessment based on the evaluation of the target registration error on synthetic data as well as a qualitative assessment on real patient data. We demonstrate that the proposed registration method provides good results in terms of both accuracy and robustness w. r. t. the quality of the intra-operative data.