Arnaud Charnoz

Tree matching applied to vascular system

In this paper, we propose an original tree matching algorithm for intra-patient hepatic vascular system registration. The vascular systems are segmented from CT-Scan images acquired at different time, and then modeled as trees. The goal of this algorithm is to find common bifurcations (nodes) and vessels (edges) in both trees. Starting from the tree root, edges and nodes are iteratively matched. The algorithm works on a set of matching hypotheses which is updated to keep best matches. It is robust against topological modification, as the segmentation process can fail to detect some branches. Finally, this algorithm is validated on the Visible Human with synthetic deformations thanks to the simulator prototype developed at the INRIA which provides realistic deformations for liver and its vascular network.

Virtual reality and augmented reality applied to laparoscopic and notes procedures

Computer-assisted surgery led to a major improvement in medicine. Such an improvement can be summarized in three major steps. The first one consists in an automated 3D modelling of patients from their medical images. The second one consists in using this modelling in surgical planning and simulator software offering then the opportunity to train the surgical gesture before carrying it out. The last step consists in intraoperatively superimposing preoperative data onto the real view of patients. This augmented reality provides surgeons a view in transparency of their patient allowing to track instruments and improve pathology targeting. We will present here our results in these different domains applied to laparoscopic and NOTES procedures.

Liver registration for the follow-up of hepatic tumors

In this paper we propose a new two step method to register the liver from two acquisitions. This registration helps experts to make an intra-patient follow-up for hepatic tumors. Firstly, an original and efficient tree matching is applied on different segmentations of the vascular system of a single patient. These vascular systems are segmented from CT-scan images acquired (every six months) during disease treatement, and then modeled as trees. Our method matches common bifurcations and vessels. Secondly, an estimation of liver deformation is computed from the results of the first step. This approach is validated on a large synthetic database containing cases with various deformation and segmentation problems. In each case, after the registration process, the liver recovery is very accurate (around 95%) and the mean localization error for 3D landmarks in liver is small (around 4 mm).

Design of robust vascular tree matching: validation on liver

In this paper, we propose an original and efficient tree matching algorithm for intra-patient hepatic vascular system registration. Vascular systems are segmented from CT-scan images acquired at different times, and then modeled as trees. The goal of this algorithm is to find common bifurcations (nodes) and vessels (edges) in both trees. Starting from the tree root, edges and nodes are iteratively matched. The algorithm works on a set of match solutions that are updated to keep the best matches thanks to a quality criterion. It is robust against topological modifications due to segmentation failures and against strong deformations. Finally, this algorithm is validated on a large synthetic database containing cases with various deformation and segmentation problems.

Portal Vein Registration for the Follow-Up of Hepatic Tumours

In this paper, we propose an original method which permits a follow-up of intra-patient evolution of tumours in the liver by using a registration of the portal vascular system.

A levelset based method for segmenting the heart in 3D+T gated SPECT images

Levelset methods were introduced in medical images segmentation by Malladi et al. in 1995. In this paper, we propose several improvements of the original method to speed up the algorithm convergence and to improve the quality of the segmentation in the case of cardiac gated SPECT images. We studied several evolution criterions, taking into account the dynamic property of heart image sequences. For each step of the segmentation algorithm, we have compared different solutions in order to both reduce time and improve quality. We have developed a modular segmentation tool with 3D+T visualization capabilities to experiment the proposed solutions and tune the algorithm parameters. We show segmentation results on both simulated and real SPECT images.

A low cost simulator to practice ultrasound image interpretation and probe manipulation: Design and first evaluation

Ultrasonography is the lowest cost no risk medical imaging technique. However, reading an ultrasound (US) image as well as performing a good US probe positioning remain difficult tasks. Education in this domain is today performed on patients, thus limiting it to the most common cases and clinical practice. In this paper, we present a low cost simulator that allows US image practice and realistic probe manipulation from CT data. More precisely, we tackle in this paper the issue of providing a cost effective realistic interface for the probe manipulation with a basic haptic feedback.

Toward Accurate Segmentation of the LV Myocardium and Chamber for Volumes Estimation in Gated SPECT Sequences

The left ventricle myocardium and chamber segmentation in gated SPECT images is a challenging problem. Segmentation is however the first step to geometry reconstruction and quantitative measurements needed for clinical parameters extraction from the images. New algorithms for segmenting the heart left ventricle myocardium and chamber are proposed. The accuracy of the volumes measured from the geometrical models used for segmentation is evaluated using simulated images. The error on the computed ejection fraction is low enough for diagnosis assistance. Experiments on real images are shown.

Computer-Assisted Digestive Surgery

Introducing an optical device into the abdomen of a patient so as to carry out the surgical procedure via a miniaturized camera represented the major change the surgical world experienced during the twentieth century: the “minimally invasive” surgery era was born. This revolution is about to experience a new twist linked to the appearance of a new original technique called Natural Orifice Transluminal Endoscopic Surgery (NOTES) that could replace traditional laparoscopic surgery for a large set of procedures. By replacing the rigid optic that is introduced through the skin by a flexible optic that is introduced through a natural orifice such as stomach, vagina or colon, this new technique should eliminate all visible incisions.