Georg Berks

Supra- and Infrasylvian Conduction Aphasia ☆

Fifteen cases of conduction aphasia which were tested with the Aachen Aphasia Test (AAT), are presented. The CT lesion data were transformed to a standard 3D-reference brain referring to the ACPC line. According to the lesion profiles a group of 6 patients had pure suprasylvian lesions, a group of 4 patients had pure infrasylvian lesions, and a group of 5 patients had lesions in both supra- and infrasylvian regions. Suprasylvian conduction aphasics are superior to infrasylvian conduction aphasics in the token test and in repetition tasks. Infrasylvian conduction aphasics use more stereotypes in spontaneous speech than suprasylvian conduction aphasics. Conduction aphasics with both lesion sites perform less well in tests of naming, writing, and comprehension than the pure types. Thus conduction aphasia is a heterogeneous syndrome anatomically and linguistically.

Visualization of nerve fiber orientation in gross histological sections of the human brain.

Diffusion weighted magnetic resonance imaging (DWMRI) allows visualization of the orientation of the nervous fibers in the living brain. For comparison, a method was developed to examine the orientation of fibers in histological sections of the human brain. Serial sections through the entire human brain were analyzed regarding fiber orientation using polarized light. Direction of fibers in the cutting plane was obtained by measuring the azimuth with the lowest intensity value at each point, and inclination of fibers in the section was evaluated using fuzzy logic approximations. Direction and inclination of fibers revealing their three‐dimensional orientation were visualized by colored arrows mapped into the images. Using this procedure, various fiber tracts were identified (pyramidal tract, radiatio optica, radiatio acustica, arcuate fascicle, and 11 more). Intermingled fibers could be separated from each other. The orientation of the fiber tracts derived from polarized light microscopy was validated by confocal laser scanning microscopy in a defined volume of the internal capsule, where the fiber orientation was studied in four human brains. The polarization method visualizes the high degree of intermingled fiber bundles in the brain, so that distinct fiber pathways cannot be understood as solid, compact tracts: Neighbouring bundles of fibers can belong to different systems of fibers distinguishable by their orientation. Microsc. Res. Tech. 51:481–492, 2000.

The application of fuzzy-based methods to central nerve fiber imaging

This paper discusses the potential of fuzzy logic methods within medical imaging. Technical advances have produced imaging techniques that can visualize structures and their functions in the living human body. The interpretation of these images plays a prominent role in diagnostic and therapeutic decisions, so physicians must deal with a variety of image processing methods and their applications. This paper describes three different sources of medical imagery that allow the visualization of nerve fibers in the human brain: (1) an algorithm for automatic segmentation of some parts of the thalamus in magnetic resonance images based on the differences in myelin content in various thalamic subnuclei; (2) polarized light for classifying the 3D orientation of the nerve fibers at each point; and (3) confocal laser scanning microscopy (CLSM) for calculating semiquantitative variables for myelin content. Fuzzy logic methods were applied to analyze these pictures from low- to high-level image processing. The solutions presented here are motivated by problems of routine neuroanatomic research demonstrating fuzzy-based methods to be valuable tools in medical image processing.

Spatial registration of digital brain atlases based on fuzzy set theory

We present a semiautomatic method based on fuzzy set theory for adjusting a computerized brain atlas to magnetic resonance images (MRIs) of the human cerebral cortex. The atlas was registered to three-dimensional MRI data sets of 10 healthy volunteers. After a global matching using the external contour of the brain, several local procedures were performed regarding selected primary furrows and cytoarchitectonic areas. The final transformation matrix was calculated with respect to these anatomical structures and to their local matrices. Evaluation revealed an increase in accuracy as expressed by a reduction of the visible mismatch with respect to the registration of cortical and subcortical brain structures.

Fuzzy sets in human anatomy

Artificial intelligence will have a great impact on the rather traditional field of anatomy. Techniques of artificial intelligence can advance anatomical research in a wide range of applications. Fuzzy logic is especially useful in facilitating the use of natural language in the mathematical description of structures or functions. Examples presented demonstrate the broad use of information technology in anatomical applications, including description and classification, knowledge representation, image processing, and three-dimensional anatomical atlases.

Fuzzy Sets in Medical Image Processing

This article describes some aspects of fuzzy methodology and their possible application in the medical community. Fuzzy methods can be arranged according to the hierarchy of medical image processing procedures to allow a convenient comparison with competitive crisp methods. Several examples are explained derived from all the three levels of image processing. Histogram evaluation using fuzzy expective value is a possible application of low level image processing. Structure and function of linguistic variables as aspects of an intermediate level are explained in some detail because of their peculiar ability to cope with uncertainties. A major problem in high level medical image processing is dealt with, when anatomic atlases are superimposed on the highly variable human brain. Finally, a method of comparing distinctive features of anatomical structure is presented.