Hemorrhage detection in MRI brain images using images features

Abstract

Abstract. The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid -sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

Modified cuckoo search algorithm in microscopic image segmentation of hippocampus

“…In addition, a comparative study can be performed including other standard segmentation techniques. The proposed method can be compared to other segmentation methods, such as those reported by Moraru, Moldovanu, Bibicu, and Stratulat (2013) and Moldovanu, Moraru, and Biswas (2015) and Zemmal (2016).…”

Magnetic Field Gradients and Their Effects on the Diffusion Tensor Derivate Measures

“…In order to increase the sensitivity of our analysis, a systematic inter-hemispheres analysis between a healthy brain and ICH alterations in brain diffusion tensor images is performed [12,13].…”