Jeanpierre Guédon

Mojette cryptomarking scheme for medical images

This paper describes a new kind of use for image watermarking. A stream watermarking method is presented, in which a key allows the authorized users to recover the original image. Our algorithm exploits the redundancy properties of the Mojette Transform. This transform is based on a specific discrete version of the Radon transform with an exact inversion. Anyone whom knows the watermark key will be able to decode the original image whereas only a marked image can be decoded without this key. The presented algorithm is suitable for different applications when fragile and reversible watermarks are mandatory such as medical image watermarking, and it could also be used for a data access scheme (cryptography). A multiscale watermark variation is presented and can be used when different user profile levels are encountered.

Spline-Based Regularization for Discrete FBP Reconstruction

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.

Statistical model for tomographic reconstruction methods using spline functions

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.

Separable and radial bases for medical image processing

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.

New automatic quality control methods for geometrical treatment planning system tools in external conformal radiotherapy

Quality control of external conformal radiotherapy treatment planning systems softwares is a crucial issue. The treatment quality depends directly on the quality of treatment planning systems (TPS). Radiotherapists need to be sure that softwares compute accurately each parameter of the treatment. This paper focuses on the quality control of geometrical tools of the treatment planning systems, i.e. the virtual simulation software. These TPS compute the geometrical part of the treatment. They define the targets and shapes of the irradiation beams. Four operations done by these TPS are examined in this work. The quality control of the auto-contouring, auto-margin, isocenter computation and collimator conformation tools is treated with a new method based on Digital Test Objects (DTO). Standard methods for this quality control have been set up from the development of some Physical Test Objects (PTO). These methods are time-consuming, incomplete and inaccurate. Results are biased by the CT-scanner acquisition of PTOs and error evaluation is done with the graphic tools of the TPS. Our method uses DTOs and allows for an automated qualitative error evaluation. DTOs present many advantages for TPS quality control. They lead to a fast, accurate, complete and automatic quality assessment. Special DTOs have been developed to control the TPS tools mentioned previously as well as their automatic result analysis methods. A TPS has been controlled with these test objects. The quality assessment shows some errors and highlights some particularities in the TPS tools functioning. This quality control was then compared with the standard quality control.

ATM-based multimedia reporting system for emergency imaging procedures

In this paper, we present a multimedia, ATM network based approach to generating and transmitting imaging procedure multimedia (MmR) reports in emergency situations. This approach was applied to V/P lung scintigrams in our institution. The architecture of our multimedia reporting system consists of a (gamma) -camera providing V/P lung scintigram as Interfile formatted data, a workstation in which MmRs can be generated and from which they can be accessed, a set of low cost workstations where MmR can be displayed, and an ATM network running throughout our hospital and connecting the above stations. The main features of the MmR are detailed in the paper and are assessed from a physician point of view.

Discrete image stacks verifying the diffusion equation for mulitresolution image processing

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.

Object-oriented image data model for a knowledge-based image processing system

For the last two years, we have been developing a medical image processing system driven by a knowledge-based system, which has been partially presents at the last SPIE Medical Imaging conference. In short, it consists of three modules: (1) an expert system (ES) which handles generic knowledge about image processing, image sources and medicine, and specific knowledge for every developed application. Consequently, it knows why, under which circumstances and in which environment an image processing tool must be achieved. (2) a relational data base (rDB) on which the ES may perform requests to select image data for an application. (3) an image processing (IP) toolbox which is able to run procedures according to the ES specifications on data pointed to by the rDB. In other words the IP toolbox knows how to run a procedure but not why.

Spline-based tomographic reconstruction method

In this paper, a new approach to the Filtered BackProjection (FBP) algorithm is presented. The method is based on the reconstruction stability in Sobolev spaces and B-spline functions which define a Pixel Intensity Distribution Model (PIDM-n) according to the spline degree n of the desired reconstruction. It is shown that PIDM-n reconstructions can be efficiently obtained. Angular sampling is studied and comparison with standard FBP shows the superiority of the algorithm presented. Moreover, simulation studies of noise degradation and blur in the projections show the algorithm to be superior to FBP in this more realistic case.