Proceedings of the 10th International

ABSTRACT Intensive Programs (IP) have been organized by four European partner universities. The main idea is to gather approximately 40 students and 15 teachers together for three weeks to conceive, design, implement, and operate embedded system prototypes. Self-evaluation is an integrated part of the IP. The results of the evaluations are used to improve the concept, content, and practical arrangements for the next IP. The same partner network has organized similar intensive projects with different topics, but using the same internal evaluation method. We can recognize issues which make the IP successful and are common to the intensive project concept, independent of the topic. Based on the evaluation material, we will make some recommendations that can help organize similar intensive projects in the future

Segmentation of Ischemic Stroke in CT Images of Human Brain

The paper deals with the problem of segmentation of ischemic stroke in the human brain computer tomography images. Carried out thorough analysis of stroke regions in images shows up several useful features that can be used in early but rough image pre-processing stages. Based on these features a procedure for segmentation of ischemic stroke regions from 2D~images into 3D~shape is developed, presented and proved by experimentation.It can be used for evaluation of stroke volume and support the decision making about patient disability

Segmentation of Ischemic Stroke in CT Images of Human Brain

The paper deals with the problem of segmentation of ischemic stroke in the human brain computer tomography images. Carried out thorough analysis of stroke regions in images shows up several useful features that can be used in early but rough image pre-processing stages. Based on these features a procedure for segmentation of ischemic stroke regions from 2D~images into 3D~shape is developed, presented and proved by experimentation.It can be used for evaluation of stroke volume and support the decision making about patient disability

Segmentation of Ischemic Stroke in CT Images of Human Brain

The paper deals with the problem of segmentation of ischemic stroke in the human brain computer tomography images. Carried out thorough analysis of stroke regions in images shows up several useful features that can be used in early but rough image pre-processing stages. Based on these features a procedure for segmentation of ischemic stroke regions from 2D~images into 3D~shape is developed, presented and proved by experimentation.It can be used for evaluation of stroke volume and support the decision making about patient disability

Automatic ischemic stroke segmentation using various techniques

Seven different methods aiming at automatic segmentation of human brain ischemic area in the computerized tomography scans are compared. The novel technique, based on the biologically inspired artificial neural networks architecture, is applied for the brain ischemic stroke recognition. The segmentation techniques were evaluated by the experts radiologists. The best viability showed Histogram, Gray level co-occurrence matrix, Mean and standard deviation methods, and Supervised Artificial Neural Networks techniquesKauno technologijos universitetasVilniaus Gedimino technikos universiteta