Functional magnetic resonance imaging (fMRI) simulator

Download
index.pdf
2015
Arslankoz, Kamil
Show full item record
264
views
98
downloads
Functional magnetic resonance imaging (fMRI) utilizes the change in the oxygenation of blood to predict active areas in the brain. fMRI consists of multiple low resolution whole brain images, for which, the contrast difference in corresponding voxels among all images are studied. In this study, an fMRI simulator has been developed which generates customized 4D fMRI data that can be used as a ground truth for comparing/benchmarking different fMRI analysis methods. This simulator can be also used for educational purposes for hands-on study of several aspects of the fMRI time series. Some of the strengths of this simulator with respect to other simulators are as follows. The simulator is programmed in MATLAB and it contains a GUI which facilitates its use. It allows an atlas (ICBM) to generate multiple brain activations within pre-defined anatomical structures. It utilizes T2 MRI images to construct task related (event/block/mixed paradigms) or DMN (Default Mode Network) 4D fMRI data. It is capable of simulating the effects of head movement, habituation, scanner drift and Gaussian noise. The simulator completes realistic fMRI data generation on the order of minutes. The results produced by the simulator are analyzed by popular fMRI analysis tools, FSL and AFNI. The estimation of brain activations and the prediction of the embodied artifacts by FSL and AFNI matched the simulation parameters with great certainty, verifying the quality of the simulations.
Brain, Brain, Magnetic resonance imaging., Cross-sectional imaging., Diagnostic imaging.
http://etd.lib.metu.edu.tr/upload/12618989/index.pdf
https://hdl.handle.net/11511/25106
Graduate School of Informatics, Thesis

Suggestions

An Information theoretic representation of brain connectivity for cognitive state classification using functional magnetic resonance imaging
Önal, Itır; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2013)
In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various info...
Convolutional neural network based brain MRI segmentation
Baydar, Bora; Akar, Gözde; Department of Electrical and Electronics Engineering (2018)
Visualization of the inner parts of human body is crucial in modern medicine and magnetic resonance imaging(MRI) is one of the widely used medical imaging methods. Manual analysis of MRIs, however, wastes the valuable time of experts. Development of an automatic segmentation method for brain MRIs can save time spent by the experts and can avoid human error factor. In this thesis, convolutional neural network (CNN) based methods are applied on brain MRI segmentation problem. The basic architectures used are ...
Improving the sub-cortical gm segmentation using evolutionary hierarchical region merging
Çiftçioğlu, Mustafa Ulaş; Gökçay, Didem; Department of Medical Informatics (2011)
Segmentation of sub-cortical Gray Matter (GM) structures in magnetic resonance brain images is crucial in clinic and research for many purposes such as early diagnosis of neurological diseases, guidance of surgical operations and longitudinal volumetric studies. Unfortunately, the algorithms that segment the brain into 3 tissues usually suffer from poor performance in the sub-cortical region. In order to increase the detection of sub-cortical GM structures, an evolutionary hierarchical region merging approa...
Coil sensitivity map calculation using biot-savart law at 3 tesla and parallel imaging in MRI
Esin, Yunus Emre; Alpaslan, Ferda Nur; Department of Computer Engineering (2017)
Coil spatial sensitivity map is considered as one of the most valuable data used in parallel magnetic resonance imaging (MRI) reconstruction. In this study, a novel sensitivity map extraction method is introduced for phased-array coils. Proposed technique uses Biot-Savart law with coil shape information and low-resolution phase image data to form sensitivity maps. The performance of this method has been tested in the parallel image reconstruction task using sensitivity encoding technique. In MRI, coil sensi...
Statistical disease detection with resting state functional magnetic resonance imaging
Öztürk, Ebru; İlk Dağ, Özlem; Department of Statistics (2017)
Most of the functional magnetic resonance imaging (fMRI) data are based on a particular task. The fMRI data are obtained while the subject performs a task. Yet, it's obvious that the brain is active even when the subject is not performing a task. Resting state fMRI (R-fMRI) is a comparatively new and popular technique for assessing regional interactions when a subject is not performing a task. This study focuses on classifying subjects as healthy or diseased with the diagnosis of schizophrenia by analyzing ...
Citation Formats
K. Arslankoz, “Functional magnetic resonance imaging (fMRI) simulator,” M.S. - Master of Science, Middle East Technical University, 2015.
METU IIS - Integrated Information Service open@metu.edu.tr