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Biomedical subjects

Stéphane Bonnet

Publications and source records attributed to Stéphane Bonnet.

5 recordsLinked to original sources
PubMed2005

[Echoendoscopic ultrasound/fine needle aspiration of an hepatic cystadenoma].

The diagnosis of hepatic cystadenoma is difficult with the conventional radiologic imaging. When these hepatobiliary cystic tumors are located in the left liver, Echoendoscopic ultrasound/Fine needle aspiration can help in the diagnosis by showing high levels of cystic CEA and CA 19-9 in a mucinous fluid. Definitive histological evaluation is assessed by the examination of the operative specimen.

Biopsy, Needle↗
PubMed2003

Nonseparable wavelet-based cone-beam reconstruction in 3-D rotational angiography.

In this paper, we propose a new wavelet-based reconstruction method suited to three-dimensional (3-D) cone-beam (CB) tomography. It is derived from the Feldkamp algorithm and is valid for the same geometrical conditions. The demonstration is done in the framework of nonseparable wavelets and requires ideally radial wavelets. The proposed inversion formula yields to a filtered backprojection algorithm but the filtering step is implemented using quincunx wavelet filters. The proposed algorithm reconstructs slice by slice both the wavelet and approximation coefficients of the 3-D image directly from the CB projection data. The validity of this multiresolution approach is demonstrated on simulations from both mathematical phantoms and 3-D rotational angiography clinical data. The same quality is achieved compared with the standard Feldkamp algorithm, but in addition, the multiresolution decomposition allows to apply directly image processing techniques in the wavelet domain during the inversion process. As an example, a fast low-resolution reconstruction of the 3-D arterial vessels with the progressive addition of details in a region of interest is demonstrated. Other promising applications are the improvement of image quality by denoising techniques and also the reduction of computing time using the space localization of wavelets.

Algorithms↗
PubMed2002

Theoretical framework for a dynamic cone-beam reconstruction algorithm based on a dynamic particle model.

Dynamic cone-beam reconstruction algorithms are required to reconstruct three-dimensional (3D) image sequences on dynamic 3D CT combining multi-row two-dimensional (2D) detectors and sub-second scanners. The speed-up of the rotating gantry allows one to improve the temporal resolution of the image sequence, but at the same time, it implies increase in the dose delivered during a given time period to keep constant the signal-to-noise ratio associated with each frame. The alternative solution proposed in this paper is to process data acquisition on several half-turns in order to reduce the dose delivered per rotation with the same signal-to-noise ratio. In order to compensate for time evolution and motion artefacts, we propose to use a dynamic particle model to describe the object evolution during the scan. In this article, we first introduce the dynamic particle model and the dynamic CT acquisition model. Then, we explain the principle of the proposed dynamic cone-beam reconstruction algorithm. Lastly, we present preliminary results on simulated data.

Algorithms↗