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In this paper we propose an efficient sparse reconstruction scheme for the parallel MRSI data acquired using a fast spiral scheme. We model the system using the MR priors estimated from the water reference scan. In our sparse reconstruction approach, we minimize the total variation and ℓ1 norm of the compartmentalized MRSI data in order to reduce noise, inhomogeneity distortions, and spectral leakage...
The aim of this study is to reveal the discriminative potential of energy related metabolites in brain gliomas classification. The proposed analysis considers two aspects, the statistical and biological verification of metabolites' effects. In particular, Magnetic Resonance Spectroscopic Imaging (MRSI) is first employed for the statistical evaluation of metabolites. Five of the identified significant...
Magnetic resonance spectroscopic imaging (MRSI) integrates both spectroscopic and imaging methods to produce spatially localized spectra from within the sample or patient. Although MRSI is a relatively new imaging technology for clinical applications and relevant databases still do not exist, the rapid advances made in the field of NMR and the associated scanning technologies, the increased frequency...
Nuclear magnetic resonance has been successfully used for the grading and typing of brain tumors. Magnetic resonance (MR) or nuclear magnetic resonance (NMR) has been widely used in hospital since the 80's. Magnetic resonance spectroscopy (MRS) is one of the main fields of MR. Our objective was to propose a classifier to ensures higher reliability and reduces time and expense costs by introducing...
In vivo 31P MRS provides non-invasive information about the chemical content of the energy metabolism in cellular level, which is important either in diagnosis or in treatment of many hepatic diseases. In this paper we applied Fisher linear discriminant analysis and quadratic discriminant analysis to classify the data samples based on 31P MRS into three types of hepatocellular carcinoma, hepatic cirrhosis...
Proton magnetic resonance spectroscopic imaging (MRSI) provides spatial information about tissue metabolite concentrations used in differentiating diseased from normal tissue. Obtaining metabolic maps with high spatial resolution requires long acquisition time where the patient has to lie still inside the magnet bore (scanner) especially if classical Chemical Shift Imaging (CSI) is used. To reduce...
Brain metastases and glioblastoma multiforme are the most aggressive and common brain tumours in adults and they require a different clinical management. Anatomical magnetic resonance imaging (MRI) or clinical history, cannot always clearly distinguish between them. This study describes and verifies the use of magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging (MRSI)...
The following topics are dealt with: advanced medical imaging technique; PET/SPECT/CT imaging; advanced detection-and-imaging technique; molecular imaging technique; nuclear medicine technique; electrical capacitance tomography and its industrial applications; optical imaging system; image analysis-and-measurement; advanced signal processing for MRS; and MRI systems.
Magnetic Resonance Spectroscopy (MRS) and Magnetic Resonance Spectroscopic Imaging (MRSI) are useful tools when used in combination with standard imaging methods that may offer a significant advantage in certain clinical applications such as cancer localization and staging. Incorporation of these tools in clinical practice is, however, limited due to the considerable amount of user intervention that...
Most hospitals are nowadays equipped with 1.5T or even 3T scanners and the use of the different MRI modalities has become widespread for diagnosis and treatment planning. However, MRS is still little used in clinical practice. For this, methods to aid radiologists in interpreting the MRS signal have been developed. The INTERPRET decision-support system, designed with this aim, will be discussed.
Tissue deterioration as induced by disease can be viewed as a continuous change of tissue from healthy to diseased and hence can be modeled as a non-linear manifold with completely healthy tissue at one end of the spectrum and fully abnormal tissue such as lesions, being on the other end. The ability to quantify this tissue deterioration as a continuous score of tissue abnormality will help determine...
In this paper, we focus on the reconstruction of iDQC MR spectroscopy data. Unlike standard 1-D MR spectroscopy schemes, iDQC acquires 2-D spectral data to decouple the magnetic field inhomogeneity effects from chemical shift information. This method suffers from a few limitations such as low intrinsic SNR, long acquisition time and the presence of a strong residual water peak. The standard IFFT based...
This paper presents a methodology to estimate the parameters of two-dimensional damped/undamped exponentials from high complexity noisy signals, which is the case in 2-D nuclear magnetic resonance spectroscopy signals. The proposed approach performs adaptive subband decomposition combined with a classical frequency estimator based on the Prony model. At each node resulting from the decomposition tree,...
We aim to integrate the chemical properties sensed by magnetic-resonance spectroscopy (MRS) with the micro-architectural mechanical properties sensed by ultrasound spectra to enhance our classifier sensitivity and specificity for distinguishing between cancerous and noncancerous regions in the prostate. Successfully combining ultrasound spectral parameters with MRS parameters, requires spatially co-registering...
Pattern recognition techniques are widely used in the biomedical domain, solving problems ranging from the prediction of cancers to the detection of neural activations in the human brain. Modern biomedical techniques, such as magnetic resonance spectroscopy (MRS) or imaging (MRI), produce voluminous, high-dimensional datasets, whose reliable analysis by medical practitioners requires high-performance,...
Prostate cancer is one of the leading causes of death in men. Accurate segmentation of prostate magnetic resonance imagery allows for the maximum volume of the prostate to be considered in diagnosis, using magnetic resonance spectroscopy, and in treatment using intensity modulated radiotherapy. In this work a semi-automatic method which segments the prostate on magnetic resonance images is presented...
De-noising the MRS data is a key processing in analysis of spectroscopy MRS data. This paper presents an effective method based on wavelet-transform and pattern recognition technologies. Upon the characteristics of MRS data, a new wavelet basis function was designed, and a de-noising method of free induction decay (FID) data using wavelet threshold to obtain better MRS spectrums was conduced; hence,...
Recently, magnetic resonance imaging and proton magnetic resonance spectroscopy studies of major depression identified structural and neurochemical alterations in several brain regions, including the hippocampus and prefrontal cortex. However, many contradictory endings exist. Most previous studies used a few cases and features, and conventional statistics. Therefore, we decided to use computational...
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