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Brain atrophy progress detection in MR images

100%

Kuczyński K. , Stęgierski R. , Siczek M.

tom Vol. 16

187--192

Alzheimer's, Parkinson's and other dementive diseases currently pose an important social problem. High brain atrophy level is one of the most important symptoms of these disorders, but it also may result from normal ageing processes. The purpose of the presented research is to design methods that support detection of dementia symptoms in radiological images. The proposed framework consists of image registration procedure, brain extraction and tissue segmentation and the exact analysis of image series (fractal and volumetric properties).

Magnetic resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms

84%

Kabir Anaraki A. , Ayati M. , Kazemi F.

tom Vol. 39, no. 1

63--74

Gliomas are the most common type of primary brain tumors in adults and their early detection is of great importance. In this paper, a method based on convolutional neural networks (CNNs) and genetic algorithm (GA) is proposed in order to noninvasively classify different grades of Glioma using magnetic resonance imaging (MRI). In the proposed method, the architecture (structure) of the CNN is evolved using GA, unlike existing methods of selecting a deep neural network architecture which are usually based on trial and error or by adopting predefined common structures. Furthermore, to decrease the variance of prediction error, bagging as an ensemble algorithm is utilized on the best model evolved by the GA. To briefly mention the results, in one case study, 90.9 percent accuracy for classifying three Glioma grades was obtained. In another case study, Glioma, Meningioma, and Pituitary tumor types were classified with 94.2 percent accuracy. The results reveal the effectiveness of the proposed method in classifying brain tumor via MRI images. Due to the flexible nature of the method, it can be readily used in practice for assisting the doctor to diagnose brain tumors in an early stage.