Image-based simulation of mitral valve dynamic closure including anisotropy.

Simulation of the dynamic behavior of mitral valve closure could improve clinical treatment by predicting surgical procedures outcome. We propose here a method to achieve this goal by using the immersed boundary method. In order to go towards patient-based simulation, we tailor our method to be adapted to a valve extracted from medical image data.

Capturing contact in mitral valve dynamic closure with fluid-structure interaction simulation.

Purpose: Realistic fluid-structure interaction (FSI) simulation of the mitral valve opens the way toward planning for surgical repair. In the literature, blood leakage is identified by measuring the flow rate, but detailed information about closure efficiency is missing. We present in this paper an FSI model that improves the detection of blood leakage by building a map of contact.

Automatic extraction of the mitral valve chordae geometry for biomechanical simulation.

Purpose: Mitral valve computational models are widely studied in the literature. They can be used for preoperative planning or anatomical understanding. Manual extraction of the valve geometry on medical images is tedious and requires special training, while automatic segmentation is still an open problem.

WatchPose: A View-Aware Approach for Camera Pose Data Collection in Industrial Environments.

Collecting correlated scene images and camera poses is an essential step towards learning absolute camera pose regression models. While the acquisition of such data in living environments is relatively easy by following regular roads and paths, it is still a challenging task in constricted industrial environments. This is because industrial objects have varied sizes and inspections are usually carried out with non-constant motions.

Elastic Registration Based on Compliance Analysis and Biomechanical Graph Matching.

An automatic elastic registration method suited for vascularized organs is proposed. The vasculature in both the preoperative and intra-operative images is represented as a graph. A typical application of this method is the fusion of pre-operative information onto the organ during surgery, to compensate for the limited details provided by the intra-operative imaging modality (e.

Biomechanics-based graph matching for augmented CT-CBCT.

Purpose: Augmenting intraoperative cone beam computed tomography (CBCT) images with preoperative computed tomography data in the context of image-guided liver therapy is proposed. The expected benefit is an improved visualization of tumor(s), vascular system and other internal structures of interest.

Method: An automatic elastic registration based on matching of vascular trees extracted from both the preoperative and intraoperative images is presented.

Multimodal acquisition of articulatory data: Geometrical and temporal registration.

Acquisition of dynamic articulatory data is of major importance for studying speech production. It turns out that one technique alone often is not enough to get a correct coverage of the whole vocal tract at a sufficient sampling rate. Ultrasound (US) imaging has been proposed as a good acquisition technique for the tongue surface because it offers a good temporal sampling, does not alter speech production, is cheap, and is widely available.

Monocular 3D Reconstruction and Augmentation of Elastic Surfaces with Self-Occlusion Handling.

This paper focuses on the 3D shape recovery and augmented reality on elastic objects with self-occlusions handling, using only single view images. Shape recovery from a monocular video sequence is an underconstrained problem and many approaches have been proposed to enforce constraints and resolve the ambiguities. State-of-the art solutions enforce smoothness or geometric constraints, consider specific deformation properties such as inextensibility or resort to shading constraints.

Impact of Soft Tissue Heterogeneity on Augmented Reality for Liver Surgery.

This paper presents a method for real-time augmented reality of internal liver structures during minimally invasive hepatic surgery. Vessels and tumors computed from pre-operative CT scans can be overlaid onto the laparoscopic view for surgery guidance. Compared to current methods, our method is able to locate the in-depth positions of the tumors based on partial three-dimensional liver tissue motion using a real-time biomechanical model.

Deformation-based augmented reality for hepatic surgery.

In this paper we introduce a method for augmenting the laparoscopic view during hepatic tumor resection. Using augmented reality techniques, vessels, tumors and cutting planes computed from pre-operative data can be overlaid onto the laparoscopic video. Compared to current techniques, which are limited to a rigid registration of the pre-operative liver anatomy with the intra-operative image, we propose a real-time, physics-based, non-rigid registration.

Statistical modeling and recognition of surgical workflow.

In this paper, we contribute to the development of context-aware operating rooms by introducing a novel approach to modeling and monitoring the workflow of surgical interventions. We first propose a new representation of interventions in terms of multidimensional time-series formed by synchronized signals acquired over time. We then introduce methods based on Dynamic Time Warping and Hidden Markov Models to analyze and process this data.

A methodology for validating a 3D imaging modality for brain AVM delineation: application to 3DRA.

A general methodology is described to validate a 3D imaging modality with respect to 2D digital subtracted angiography (DSA) for brain AVMs (BAVM) delineation. It relies on the assessment of the statistical compatibility of the radiosurgical target delineated in 3D with its delineations in 2D. This methodology is demonstrated through a preliminary evaluation of 3D rotational angiography (3DRA).