Biomedical subjects

R Collorec

Publications and source records attributed to R Collorec.

7 recordsLinked to original sources

PubMed1995

[Analysis of texture in medical imaging. Review of the literature].

This paper presents a review of the applications of texture analysis in medical imaging. Many authors take a great interest in this topic (75 papers have been published since 1984) and try to elaborate automatic methods for tissue characterization. The results are not really convincing and applications are often reduced to feasibility studies. This failure is due to the empirical approach to the problem: the first studies were performed on ultrasound images, in which visual texture is very present, but no data standardization is available with this imaging modality. A more rational approach should provide better results. For each organ or tissue, it is necessary to find the appropriate source and texture analysis method. This difficult task requires reflection concerning the interactions between tissues and imaging sources, to define judicious structuring elements. These structuring elements should facilitate the choice of the best texture analysis method, for the particular application. Considerable methodological progress has yet to be made, after which texture analysis should be a useful and efficient tool for clinical use.

Humans↗

PubMed1995

[Glossary of terms used by radiologists in image processing].

We give the definition of 166 words used in image processing. Adaptivity, aliazing, analog-digital converter, analysis, approximation, arc, artifact, artificial intelligence, attribute, autocorrelation, bandwidth, boundary, brightness, calibration, class, classification, classify, centre, cluster, coding, color, compression, contrast, connectivity, convolution, correlation, data base, decision, decomposition, deconvolution, deduction, descriptor, detection, digitization, dilation, discontinuity, discretization, discrimination, disparity, display, distance, distorsion, distribution dynamic, edge, energy, enhancement, entropy, erosion, estimation, event, extrapolation, feature, file, filter, filter floaters, fitting, Fourier transform, frequency, fusion, fuzzy, Gaussian, gradient, graph, gray level, group, growing, histogram, Hough transform, Houndsfield, image, impulse response, inertia, intensity, interpolation, interpretation, invariance, isotropy, iterative, JPEG, knowledge base, label, laplacian, learning, least squares, likelihood, matching, Markov field, mask, matching, mathematical morphology, merge (to), MIP, median, minimization, model, moiré, moment, MPEG, neural network, neuron, node, noise, norm, normal, operator, optical system, optimization, orthogonal, parametric, pattern recognition, periodicity, photometry, pixel, polygon, polynomial, prediction, pulsation, pyramidal, quantization, raster, reconstruction, recursive, region, rendering, representation space, resolution, restoration, robustness, ROC, thinning, transform, sampling, saturation, scene analysis, segmentation, separable function, sequential, smoothing, spline, split (to), shape, threshold, tree, signal, speckle, spectrum, spline, stationarity, statistical, stochastic, structuring element, support, syntaxic, synthesis, texture, truncation, variance, vision, voxel, windowing.

Diagnostic Imaging↗

PubMed1994

Computer vision approaches for the three-dimensional reconstruction of coronary arteries: review and prospects.

The objective of this article is to define the different stages involved in the 3D reconstruction of arteries and to review, from our experience and from the literature, the solutions already proposed. A full reconstruction framework includes the characterization of the imaging device (in terms of distortion and calibration), the specificity of the image acquisition process, the preprocessing that can be applied, the detection of the vascular structures, the 2D feature formation, the reconstruction itself, and the visualization aspects. They are examined according to a computer vision approach where two or three views are assumed to be available. Their generalization to temporal image sequences are also considered. Some of the material reported here is unpublished. The article allows the reader to identify the true critical issues that are not often clearly mentioned in the literature and the challenges that they convey. A final discussion presents a few perspectives in this area of research.

Artificial Intelligence↗

PubMed1993

Iterative reconstruction methods for nonuniform attenuation distribution in SPECT.

Two iterative methods, a generalization of the Chang method and a projection precorrection, were investigated to determine whether the use of an attenuation map could improve nonuniform attenuation compensation. After a detailed description of the methods, results obtained with simulated and phantom data were compared. This study demonstrates that projection precorrection provides accurate quantification and good image quality as early as the precorrection step, whereas the generalized Chang method requires computation of one more iteration.

Algorithms↗

PubMed1992

A framework for automatic analysis of the dynamic behaviour of coronary angiograms.

A framework for coronary vessels analysis in digital subtracted angiograms is described. This method combines the motion estimation with the frame-to-frame structure detection in a natural way such that they act interactively. The first step consists of the extraction of the vessel centrelines in one image and their organization into meaningful constituents or branches of the coronary arterial tree. The motion is then estimated along the centrelines through a gradient based method. These motion estimates supply an initial positioning of an active contour model (or 'snake') in the next image. This model adapts itself by changing its shape to accurately fit onto the new centrelines. This process is then reiterated on the subsequent images to depict the dynamic behaviour of all the relevant branches. The main interests of this scheme are: (1) the active models operate locally so a fast detection of the vessels can be performed; (2) the centrelines extraction is fully guided by the confluence of the motion estimation and the contour model; (3) both morphological and kinetic features are provided on a quantitative basis.

Algorithms↗

PubMed1988

Computer graphics in medicine: a survey.

Increased interest is presently given to three-dimensional (3-D) medical applications due to simultaneous emergence of high-resolution imaging systems and computer graphics techniques. This paper intends to present a survey of this field together with discussion and prospective views. The general framework is composed of six parts: data acquisition and preprocessing, polygonal object representation, voxel description, system architecture, medical applications, and prospects. Data base acquisition includes characterization of imaging modalities and medical specificity. Preprocessing schemes are directed to improvements (filtering), windowing, and spatial anisotropy (linear or spline interpolation). The two following sections are devoted to descriptions of the main object representations. Particular emphasis is given to optimal contour approximation, surface triangulation, mathematical surfaces on one hand, and cuberille and voxel representations on the other. Display capabilities--hidden surface removal, surface normal shading, structure enhancement--and data base structuration--hierarchical and nonhierarchical (graph and tree encoding)--are, respectively, described. An overview of 3-D systems is further given (Section V), and features of medical applications are reviewed and gathered in basic functionalities, surgery, and radiotherapy specifications (Section VI). The last section provides some prospective views on reconstruction from a few projections, model-guided labeling, multimodality image overlay, and local image network. Some of these issues are illustrated by examples of 3-D images.

Computer Graphics↗

PubMedDate not supplied

Vascular network segmentation in subtraction angiograms: a comparative study.

The three-dimensional reconstruction of vascular trees from a very limited number of two-dimensional projections is an active research field. The quality of the results (resolution in terms of vessel size and geometrical location) is highly dependent on the overall distortions introduced in the data acquisition process but is also related to the reliability of feature detection. A new approach based on mathematical morphology is proposed in this paper for extracting the centrelines and edges of coronary vessels from digital subtracted angiograms. These results are compared with those from an alternative method based on vectorial tracking and a directed contour finder.

Angiography, Digital Subtraction↗