Biomedical subjects

Philippe Thévenaz

Publications and source records attributed to Philippe Thévenaz.

4 recordsLinked to original sources

PubMed2007

User-friendly semiautomated assembly of accurate image mosaics in microscopy.

We present a semiautomated software solution to the problem of extending the lateral field of view of a classical microscope. The initial requirements are a set of overlapping images, along with their user-provided coarse mosaic. Our solution then refines this initial mosaic in a fully automatic fashion. We rely on a highly accurate registration engine to perform the pairwise registration of the individual images, and on an efficient strategy to minimize the amount of computations while maintaining the highest possible global quality. We describe these ingredients, which we make available as a free multiplatform user-friendly software package. We also highlight why and how the specific aspects of the present microscopy application differ from those encountered while creating more common mosaics such as panoramas. Finally, we present experimental results that illustrate and validate our method on a real biological sample. We conclude by showing that we are able to reach subpixel accuracy.

Algorithms↗

PubMed2005

Elastic registration of biological images using vector-spline regularization.

We present an elastic registration algorithm for the alignment of biological images. Our method combines and extends some of the best techniques available in the context of medical imaging. We express the deformation field as a B-spline model, which allows us to deal with a rich variety of deformations. We solve the registration problem by minimizing a pixelwise mean-square distance measure between the target image and the warped source. The problem is further constrained by way of a vector-spline regularization which provides some control over two independent quantities that are intrinsic to the deformation: its divergence, and its curl. Our algorithm is also able to handle soft landmark constraints, which is particularly useful when parts of the images contain very little information or when its repartition is uneven. We provide an optimal analytical solution in the case when only landmarks and smoothness considerations are taken into account. We have applied our approach to perform the elastic registration of images such as electrophoretic gels and fly embryos. The validation of the results by experts has been favorable in all cases.

Algorithms↗

PubMed2004

Linear interpolation revitalized.

We present a simple, original method to improve piecewise-linear interpolation with uniform knots: we shift the sampling knots by a fixed amount, while enforcing the interpolation property. We determine the theoretical optimal shift that maximizes the quality of our shifted linear interpolation. Surprisingly enough, this optimal value is nonzero and close to 1/5. We confirm our theoretical findings by performing several experiments: a cumulative rotation experiment and a zoom experiment. Both show a significant increase of the quality of the shifted method with respect to the standard one. We also observe that, in these results, we get a quality that is similar to that of the computationally more costly "high-quality" cubic convolution.

Algorithms↗

PubMed2003

Improvement in the quantification of myocardial perfusion using an automatic spline-based registration algorithm.

PURPOSE: To improve the quantification of myocardial perfusion by registering the time series of magnetic resonance (MR) images with injection of gadolinium. MATERIALS AND METHODS: Eight patients underwent MR scans to perform myocardial perfusion exam. Two short axis views of the left ventricle (LV) were acquired in free breathing. Two masks for performing the spatial registration of the images were evaluated. The registration was based on pixel intensity in a multi-resolution scheme. The efficiency of this correction was evaluated by calculating geometric residual displacement of the LV and by fitting the data to a compartment model fit with two parameters: K1, the blood-to-myocardium transfer coefficient, and Vd, the distribution volume of the contrast media. RESULTS: The registration stage allowed a decrease in the observed motion of the LV from more than 1.98 +/- 0.68 mm to less than 0.56 +/- 0.18 mm (mean +/- SD). Variability obtained in the perfusion analysis decreased from 46 +/- 103% to 5+/- 4% for K1 parameter and from 18 +/- 21% to 5 +/- 5% for Vd parameter. CONCLUSION: As with manual correction, this automatic motion correction leads to accurate perfusion parameters in dynamic cardiac MR imaging after contrast agent injection. This automatic stage requires placing only one mask over one frame of the perfusion study instead of manually shifting each image to fit a reference image of the perfusion study.

Algorithms↗