Observations on comatose survivors of cardiopulmonary resuscitation with generalized myoclonus

BACKGROUND: There is only limited data on improvements of critical medical care is resulting in a better outcome of comatose survivors of cardiopulmonary resuscitation (CPR) with generalized myoclonus. There is also a paucity of data on the temporal dynamics of electroenephalographic (EEG) abnormalities in these patients. METHODS: Serial EEG examinations were done in 50 comatose survivors of CPR with generalized myoclonus seen over an 8 years period. RESULTS: Generalized myoclonus occurred within 24 hours after CPR. It was associated with burst-suppression EEG (n = 42), continuous generalized epileptiform discharges (n = 5), alpha-coma-EEG (n = 52), and low amplitude (10 μV <) recording (n = 1). Except in 3 patients, these EEG-patterns were followed by another of these always nonreactive patterns within one day, mainly alpha-coma-EEG (n = 10) and continuous generalized epileptiform discharges (n = 9). Serial recordings disclosed a variety of EEG-sequences composed of these EEG-patterns, finally leading to isoelectric or flat recordings. Forty-five patients died within 2 weeks, 5 patients survived and remained in a permanent vegetative state. CONCLUSION: Generalized myoclonus in comatose survivors of CPR still implies a poor outcome despite advances in critical care medicine. Anticonvulsive drugs are usually ineffective. All postanoxic EEG-patterns are transient and followed by a variety of EEG sequences composed of different EEG patterns, each of which is recognized as an unfavourable sign. Different EEG-patterns in anoxic encephalopathy may reflect different forms of neocortical dysfunction, which occur at different stages of a dynamic process finally leading to severe neuronal loss

ROAD EXTRACTION IN SUBURBAN AREAS BASED ON NORMALIZED CUTS

This paper deals with road extraction of high resolution aerial images of suburban scenes based on segmentation using the Normalized Cuts algorithm. The aim of our project is the extraction of roads for the assessment of a road database, however, this paper is restricted to road extraction. The segmentation as our basic step is designed to yield a good division between road areas and the surroundings. We use the Normalized Cuts algorithm, which is a graph-based approach that divides the image on the basis of pixel similarities. The definition of these similarities can incorporate several features, which is necessary for the segmentation in complex surroundings such as built-up areas. The features used for segmentation comprise colour, hue, edges and road colour derived with prior information about the position of the centerline from the database. The initial segments have to be grouped due to an enforced oversegmentation. The grouping is based on the criteria of mean colour difference, edge strength of the shared borders and colour standard deviation of merged initial segments. The grouped segments are then evaluated using shape criteria in order to extract road parts. Results on some test images show that the approach provides reliable road parts. Concluding remarks are given at the end to point out further investigations concerning the evaluation of the road segments and their use in database assessment. * Corresponding author. 1

Network Snakes-Supported Extraction of Field Boundaries from Imagery

Abstract. A fully automatic method to extract field boundaries from imagery is described in this paper. The fields are represented together with additional prior knowledge in the form of GIS-data in a semantic model. The approach consists of two main steps: Firstly, a segmentation is carried out in a coarse scale resulting in preliminary field boundaries. In a second step network snakes are used to improve the geometrical correctness of the preliminary boundaries taking into account topological constraints while exploiting the local image information. Focussing on the network snakes and their specialties the results demonstrate the potential of the proposed solution.