Petra A. van den Elsen

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Describes an automated approach to register CT and MR brain images. Differential operators in scale space are applied to each type of image data, so as to produce feature images depicting "ridgeness". The resulting CT and MR feature images show similarities which can be used for matching. No segmentation is needed and the method is devoid of human(More)
Ridge-like structures in digital images may be extracted by convolving the images with derivatives of Gaussians. The choice of the convolution operator and of the parameters involved defines a specific ridge image. In this paper, various ridge measures related to isophote curvature are constructed, reviewed, and evaluated with respect to their usability in(More)
In modern medicine, several different imaging techniques are frequently employed in the study of a single patient. This is useful, since different images show complementary information on the functionality and/or structure of the anatomy examined. This very difference between modalities, however, complicates the problem of proper registration of the images(More)
Interpretation of EEG (electroencephalography) or MEG (magnetoencephalography) derived three-dimensional dipole localizations is hampered by poor visualization. This paper describes a method for combining dipole data with structural image data of the same patient. To ensure high precision this method utilizes external markers that are easy to apply. These(More)
Different structural as well as functional imaging techniques are becoming increasingly important in the investigation of patients suffering from an ischemic stroke. Available imaging procedures usually provide complementary data, but the images can not easily be compared due to differences in patient positioning, angulation, and slice thickness. We studied(More)
applications there is a need for integration of the information obtained, as different modalities usually provide complementary information. Complete comprehension of a medical case in clinician's mind is facilitated by an integrated multimodal approach. Combining the diverse sources of information is difficult, not only because of the distinct physical(More)
Geometrical image features like edges and ridges in digital images may be extracted by convolving the images with appropriate derivatives of Gaussians. The choice of the convolution operator and of the parameters of the Gaussian involved de nes a speci c feature image. In this paper, various feature images derived from CT and MR brain images are de ned and(More)
Multimodal medical images are often of too different a nature to be registered on the basis of the image grey values only. It is the purpose of this chapter to construct operators that extract similar structures from these images that will enable registration by simple grey value based methods, such as optimization of cross-correlation. These operators can(More)
This article discusses the fusion of brain images from multiple modalities as well as the presentation of the integrated image information. The paper has three parts. First, individual brain imaging modalities are compared as regards clinical appreciation, invasiveness, dimensionality, spatial resolution, temporal resolution, and cost. Next, methods to(More)