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Dive into the research topics where Yves J. Bizais is active.

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Featured researches published by Yves J. Bizais.


IEEE Transactions on Medical Imaging | 1994

Bandlimited and Haar filtered back-projection reconstructions

Jeanpierre Guédon; Yves J. Bizais

A new way to discretize the filtered back-projection (FBP) algorithm is presented. The function basis is the Haar system (2D product of rectangular windows). This scheme allows one to derive the optimal shape of the apodisation window, which is angle varying, and the oversampling ratio between the pixel and the projection cell size. The discrete equivalent filter is also derived. The comparison of standard radial band-limited and separable Haar reconstructions shows that improvements, in terms of linearity, shift-invariance and aliasing, can be obtained even for the case of a limited number of views. Considerations of projection degradations are then analyzed according to a specific imaging device to derive the optimum oversampling ratio.


Electronic Notes in Discrete Mathematics | 2005

The Mojette Transform: Discrete Angles for Tomography

Myriam Servières; Nicolas Normand; Jeanpierre Guédon; Yves J. Bizais

In this paper, a discrete geometry way to generate projection and backprojection operators useful for tomographic reconstruction schemes is presented using the Mojette transform. A generic pixel model helps to links the discrete plane to physical rays. A completely discrete exact BP-F algorithm is presented and two other (direct and iterative) methods also derived to solve the tomographic problem.


IEEE Transactions on Medical Imaging | 1998

Standardization in the field of medical image management: the contribution of the MIMOSA model

Bernard Gibaud; H. Carfagni; F. Aubry; A.T. Pokropek; Virginie Chameroy; Yves J. Bizais; R. Di Paola

This paper deals with the development of standards in the field of medical imaging and picture archiving and communication systems (PACSs), and notably concerning the interworking between PACSs and hospital information systems (HIS). It explains, in detail, how a conceptual model of the management of medical images, such as the medical image management in an open system architecture (MIMOSA) model, can contribute to the development of standards for medical image management and PACSs. This contribution is twofold: 1) Since the model lists and structures the concepts and resources involved to make the images available to the users when and where they are required, and describes the interactions between PACS components and HIS, the MIMOSA work helps by defining a reference architecture which includes an external description of the various components of a PACS, and a logical structure for assembling them. 2) The model and the implementation of a demonstrator based on this model allow the relevance of the Digital Imaging and Communications in Medicine (DICOM) standard with respect to image management issues to be assessed, highlighting some current limitations of this standard and proposing extensions. Such a twofold action is necessary in order both to bring solutions, even partial, in the short term, and to allow for the convergence, in the long term, of the standards developed by independent standardization groups in medical informatics (e.g., those within Technical Committee 251 of CEN: Comite Europeen de Normalisation).


information processing in medical imaging | 1991

Spline-Based Regularization for Discrete FBP Reconstruction

Jeanpierre Guédon; Yves J. Bizais

In this paper, we show that tomographic images are degraded by the unsuitable discretisation of continuous schemes, and the non-trivial null space in the case of angular sampling. Usually these two types of degradations are not studied separately. However, discretisation can be performed properly, while the null space is irreducible. For this reason, we study the relationships between continuous and discrete versions of a direct reconstruction method (FBP). They are characterized by an interpolation / sampling kernel, called the Pixel Intensity Distribution Model (PIDM). By defining the latter as B-spline functions, the existence and the uniqueness of the solution is guaranteed. It follows that projections must be oversampled. We test the robustness of this exact solution (for an infinite number of projections) by decreasing the number of angles. PIDM results are much better then FBP ones, showing that FBP reconstructed images are degraded not only by the null space, but also by unsuitable discretisation.


SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation | 1994

Statistical model for tomographic reconstruction methods using spline functions

Habib Benali; Jeanpierre Guédon; Irène Buvat; M. Pélégrini; Yves J. Bizais; Robert Di Paola

The conventional approach to tomographic reconstruction in the presence of noise consists in finding some compromise between the likelihood of the noisy projections and the expected smoothness of the solution, given the ill-posed nature of the reconstruction problem. Modelling noise properties is usually performed in iterative reconstruction schemes. In this paper, an analytical approach to the reconstruction from noisy projections is proposed. A statistical model is used to separate the relevant part of the projections from noise before the reconstruction. As reconstruction of sampled noise-free projections is still an ill- posed problem, a continuity assumption regarding the object to be reconstructed is also formulated. This assumption allows us to derive a spline filtered backprojection in order to invert the Radon operator. Preliminary results show the interest of combining continuity assumptions with noise modelling into an analytical reconstruction procedure.


Medical Imaging '90, Newport Beach, 4-9 Feb 90 | 1990

Projection and backprojection models, and projection sampling in tomography

Jeanpierre Guédon; Yves J. Bizais

In this paper, a continuous / discrete projection / backprojection model is presented, from which the validity of the discrete projection / reconstruction algorithm can be assessed. We mainly focus on projection sampling since angular sampling has been extensively studied previously. For this purpose a pixel intensity distribution model relating continuous and discrete original functions is proposed. Sampling of model projections is then studied, and projection filtering analyzed. Proper implementation of the discrete backprojection operator is derived, such that the resulting reconstructed function can be compared with the original one, and the overall consistency of the aproach proved. Experimental results are presented to demonstrate the validity of the theoritical approach. The consequences of properly sampling projections in practical conditions are fmally discussed.


Medical Imaging 1993: Image Processing | 1993

Separable and radial bases for medical image processing

Jeanpierre Guédon; Yves J. Bizais

The goal of this paper is to describe a consistent method which permits to define discrete image processing operators in the same way as discrete image formation operators. This is done via the use of the generalized sampling theorem which establishes the relationship between continuous and discrete functions according to the mean-square error in a spline or bandlimited subspace. A discrete operator is defined according to its continuous counterpart operating on continuous functions in the same subspace. Classical medical image acquisition bases often are radial where classical image processing operators are deduced from separable bases. The paper shows the trends between these two imperatives for medical image processing, explains where are the risks for information loss induced by implementing discrete linear operators and presents two methods to partially or totally keep the initial stored information.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.


international conference of the ieee engineering in medicine and biology society | 1992

Toward modelling image management in PACS: Lessons from a preliminary review of end-users requirements

Bernard Gibaud; Yves J. Bizais; N. Morcet; Y. Gandon; T. Buhé; Anne-Marie Forte; Florent Aubry; J. Chabriais; Virginie Chameroy; R. Di Paola; O. Ratib; A. Todd Pokropek; R. Kanz; M. Guitel; D. Vital; J. P. Ramond

The work reported in this paper has been carried out in the framework of the EURIPACS/MIMOSA AIM project. This paper reports about a preliminary review of PACS users requirements: it stresses some difficulties encountered in discussions with the users and explains how we tried to overcome them. The result of this analysis is presented and briefly discussed.


Archive | 1991

A comprehensive model for medical image data bases

Yves J. Bizais; F. Aubry; Bernard Gibaud; Jean-Marie Scarabin; R. Di Paola

Picture Archiving and Communication Systems (PACS) aim at providing an environment to store and retrieve medical images, and to distribute them. Several medical, technological and organizational problems must be solved before PACS can be introduced in clinical environments. In this paper, the specific features of (medical) images and their consequences on the development of Medical Image Data Bases (MIDB) are discussed. In particular we show that new conceptual solutions need to be found, if PACS are to provide more efficient ways of exploiting images.


Medical Imaging 1993: Image Processing | 1993

Discrete image stacks verifying the diffusion equation for mulitresolution image processing

Christophe Dary; Yves J. Bizais; Jeanpierre Guédon; Laurent Bedat

In practical situations, images are discrete and only discrete filtering can be performed, such that the above theory must be adapted accordingly. In this paper, we derive the filter family which must replace the Gaussian kernel, in this case. The result can be understood because the Fourier transform of the second derivative corresponds to the multiplication by the square of the frequency, such that our filter is the discrete version of a Gaussian. In other words, our approach consistently generalizes the continuous theory to the discrete case. When the discrete equivalent of the Laplacian is defined on the basis of n-order B-spline interpolating functions, the image stack exactly verifies the continuous diffusion equation at the spatially sampled points. These results are generalized to any linear partial differential operator corresponding to another requirement on the image stack, just by defining the discrete equivalent operator.

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Jeanpierre Guédon

Center for Devices and Radiological Health

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Jeanpierre Guédon

Center for Devices and Radiological Health

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F. Aubry

Institut Gustave Roussy

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Franck Lavaire

Centre national de la recherche scientifique

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