Ragnar Pascher

Virtual Reality and Haptics as an Assessment Device in the Postacute Phase after Stroke

Virtual reality (VR) technology is altering the health care environment and is changing the options that are available to therapists. This study describes how a haptic device was used as a cinematic assessment utility. Three chronic stroke inpatients at Sahlgrenska University Hospital with left hemisphere damage were assessed. The patients were administered by the box and block manual dexterity test. For comparisons, a reference group was added to the study. Several parameters, including time, speed, and movement of the right upper extremity, were extracted and evaluated. The results indicate that the system shows potential as an assessment device. The feasibility study setup is working well, as is the assessment method. Further research, testing, refinement of the exercises, and use of VR and haptics within neurological rehabilitation are suggested.

Aspects of the organization of neurons and dendritic bundles in primary somatosensory cortex of the rat

In order to analyze some aspects of the spatial organization in the primary somatosensory cortex of the rat, we have reconstructed the positions of bundles of apical dendrites and neurons in a cortical prisms measuring 0.5 mm x 0.4 mm x cortical thickness, with special reference to a hypothetical columnar organization. Complete series of semithin (0.65 microm) sections were cut, tangentially from the pial surface down to the white matter, stained and digitizalized into a computer and represented as a stack of 2D images. The mean neuron density (N(V)-value) was (60 x 10(3) +/- 15 x 10(3)) neurons/mm3. The mean number of neurons beneath 1 mm2 of cortical surface (NC-value) was (113 x 10(3) +/- 8 x 10(3)) neurons/mm2. Well-defined bundles of apical dendrites emanating from layer V pyramidal cells were observed. The bundles consisted of 3-12 (mean 5 +/- 2) dendrites. The dendrites within a bundle converged while ascending towards the pial surface and reached a maximal close packing in layer IV. Superficially, the packing density decreased again. The mutual positions of the dendrites within the bundles shifted only slightly along their course towards the pial surface. The occurrence of bundles in tangential sections through layer IV was about 190 bundles/mm2 and the average number of neurons per bundle was estimated at approximately 600. However, when calculating Voronoi-diagrams, the number of neurons, which with this mathematical technique, is ascribed to each of the reconstructed dendritic bundles, varied between 200 and 1000. The possibility that the dendritic bundles are centers in cortical cell modules is discussed.

Model based dynamic 3d reconstruction and display of the left ventricle from 2D cross-sectional echocardiograms

In this paper we describe a technique for dynamic three-dimensional (3D) reconstruction of the left ventricle, using boundaries from multiple two-dimensional (2D) echocardiographic views. We use a geometric model of the left ventricle and anatomical landmarks to relate the recorded views to positions within the model. The reconstruction is step-wise refined by replacing model data with recorded contour data.

3D reconstruction of biological objects from sequential image planes—Applied on cerebral cortex from cat

A prism of cat cerebral cortex was reconstructed with a method for three-dimensional (3D) representation of biological objects. A series of 918 semithin sections were digitized into an image analysis system. The images were aligned and analyzed, and a data base with the coordinates and a classification of the cells was created. The data base (i.e., the cortical prism) was visualized in a 3D graphic terminal, and parameters such as columnar and lamellar organization, clustering, and cell density were analyzed. A neuronal perikaryon and its neurites was reconstructed and shown together with the cortical prism.

Three-dimensional representation of biological objects as reconstructed from sequential image planes: Part I - the problem of image realignment

We describe a method for automatic realignment of consecutive 2-D microscopic images of brain cortex. The procedure is capable of carrying out high-quality realignment of 10 - 20 images per hour. The resulting image stack can be viewed in real-time by cinematographic animation or used for 3-D object reconstruction. The technique does not rely on expensive hardware, but can be implemented on low-cost PCs and workstations.

Three-dimensional representation of biological objects as reconstructed from sequential image planes: Part II - the reconstructed object space and its on-line integration with the image stack

A program package is described that: (1) handles a stack of several thousand aligned sequential photographic 2-D images as stored in an image processing system, (2) builds a database from information extracted from objects present in the stack of 2-D images, (3) transfers the database to an advanced graphic terminal, (4) reconstructs a 3-D object space, and (5) allows on-line interaction between the image processing system and the graphic terminal. The cell content of a prism of motor cerebral cortex of the cat is reconstructed as an application sample.

Computer-assisted 3d analysis of cell distributions in the normal and epileptic cerebral cortex: Description of a methodology in progress

This paper describes software routines that (a) visualizes a stack of several thousands of aligned sequential photographic two-dimensional (2D) images stored in an image processing system; (b) creates a data base containing information about objects identified sequentially from the 2D images; (c) transfers the data base to a graphical terminal; (d) reconstructs a three-dimensional (3D) object space; and (e) supports on-line interaction between the image processing system and the graphical terminal. As an application example, the cell content of a prism of motor cerebral cortex of the cat is reconstructed. Preliminary results from reconstructing human epileptic temporal cortex (cortical microdysgenesia) are also reported.

Automated Correction of Linear Deformation due to Sectioning in Serial Micrographs

This paper describes an objective and automatic method for detection and correction of sectioning deformations in digitized micrographs, as well as an evaluation of the method applied to light and electron microscopic images of semi‐thin and ultra‐thin serial sections from brain cortex. The detection is based on matching of image subregions and the deformation model is bi‐linear, i.e. two first‐order polynomials are used for modelling compression/expansion in perpendicular directions. The procedure is applicable to prealigned serial two‐dimensional sections and is primarily aimed at three‐dimensional reconstruction of tissue samples consisting of a large number of cells with random distribution and morphology.