1,721,152 research outputs found
The Use of the Levenberg-Marquardt and Variable Projection Curve-Fitting Algorithm in Intravoxel Incoherent Motion Method for DW-MRI Data Analysis
No full textThe objective of this study was to evaluate the performances of different algorithms for diffusion parameters estimation in intravoxel incoherent motion method for diffusion-weighted magnetic resonance imaging (DW-MRI) data analysis. Traditionally, the method of non-linear least squares analysis by means of Levenberg–Marquardt algorithms has been used to estimate the parameters obtained from exponential decay data. In this study, we evaluated the Variable Projection curve-fitting algorithm and the performance of two non-linear regression methods when single and multiple starting points were used. Analysis was done on simulation data to which different amounts of Gaussian noise had been added. The performance of two non-linear regression methods was compared using the residual sum of squares and the number of failures in data fitting. We conclude that the VarPro algorithm is superior to the LM algorithm for curve fitting in intravoxel incoherent motion method for DW-MRI data analysis
Performances of Different Algorithms for Tracer Kinetics Parameters Estimation in Breast DCE-MRI
No full textObjective of this study was to evaluate the performances of different algorithms for tracer kinetics parameters estimation in breast Dynamic Contrast Enhanced-MRI. We considered four algorithms: two non-iterative algorithms based on impulsive and linear approximation of the Arterial Input Function respectively; and two iterative algorithms widely used for non-linear regression (Levenberg-Marquardt, LM and VARiable PROjection, VARPRO). Per each value of the kinetic parameters within a physiological range, we simulated 100 noisy curves and estimated the parameters with all algorithms. Sampling time, total duration and noise level have been chosen as in a typical breast examination. We compared the performances with respect to the Cramer-Rao Lower Bound (CRLB). Moreover, in order to gain further insight we applied the algorithms to a real breast examination. Accuracy of all the methods depends on the specific value of the parameters. The methods are in general biased: however, VARPRO showed small bias in a region of the parameter space larger than the other methods; moreover, VARPRO approached CRLB and the number of iterations were smaller than LM. In the specific conditions analyzed, VARPRO showed better performances with respect to LM and to non-iterative algorithms
Accuracy of Contrast Agent Quantification in MRI: A Comparison Between Two k-space Sampling Schemes
No full textDynamic contrast-enhanced magnetic resonance imaging (DCE MRI) plays an important role in many applications, such as perfusion imaging in oncology. Several aspects of data acquisition should be taken into account when developing protocols for DCE MRI both to facilitate integration of results from multiple institutions and to ensure that the data reflect the underlying physiology as accurately as possible.In this study we focused on the trade-off between accurate contrast agent (CA) quantification ad temporal resolution. The commonly used spoiled gradient-echo k-space scheme known as Fast Low Angle SHot (FLASH) can suffer from low temporal resolution if a large field of view must be scanned. Recently, a k-space under-sampling and data-sharing method known as Time-resolved angiography With Stochastic Trajectories (TWIST) has been proposed to obtain high temporal resolution without sacrificing the spatial resolution. However, the losses in CA quantification have not been analyzed yet.The aim of this study was to evaluate the accuracy of TWIST CA quantification with respect to FLASH.Seven vials containing different Gd-DTPA solutions were prepared. Images were acquired using breast coils and several combinations of the different parameters of the two schemes analyzed. Quantification accuracy has been evaluated in terms of relative error and standard deviation. Also the repeatability for both sequence was evaluated on ten measures.The accuracy of CA quantification with both sequences depends on the specific amount of Gd-DTPA present in the prepared solutions.However, our results show that FLASH and TWIST give comparable accurac
Adaptive removal of gradients-induced artefacts on ECG in MRI: a performance analysis of RLS filtering
No full textOne of the main vital signs used in patient monitoring during Magnetic Resonance Imaging (MRI) is Electro-Cardio-Gram (ECG). Unfortunately, magnetic fields gradients induce artefacts which severely affect ECG quality. Adaptive Noise Cancelling (ANC) is one of the preferred techniques for artefact removal. ANC involves the adaptive estimation of the impulse response of the system constituted by the MRI equipment, the patient and the ECG recording device. Least Mean Square (LMS) adaptive filtering has been traditionally employed because of its simplicity: anyway, it requires the choice of a step-size parameter, whose proper value for the specific application must be estimated case by case: an improper choice could yield slow convergence and unsatisfactory behaviour. Recursive Least Square (RLS) algorithm has, potentially, faster convergence while not requiring any parameter. As far as the authors' knowledge, there is no systematic analysis of performances of RLS in this scenario. In this study we evaluated the performance of RLS for adaptive removal of artefacts induced by magnetic field gradients on ECG in MRI, in terms of efficacy of suppression. Tests have been made on real signals, acquired via an expressly developed system. A comparison with LMS was made on the basis of opportune performance indices. Results indicate that RLS is superior to LMS in several respects
A geometrical perspective on the 3TP method in DCE-MRI
No full textThe 3TP (three time points) method has been proposed for producing high-resolution pseudo-coloured maps related to the angiogenic activity in breast DCE-MRI. In the original formulation of the method, the three time-points have been chosen on an empirical basis: the algorithm for benign/malignant/uncertain classification of a voxel was to be as simple as possible and the corresponding regions of the parameters space (according to the Tofts' model) were to occupy approximately the same area. Since its inception, the method has been largely used in clinical environment, due to its simplicity and soundness. However, as only three time-points are used to evaluate the characteristics of the complex time-course of the contrast medium within capillaries, noise can result in voxel misclassification, as we show in this study.In this paper we analysed the performances of the method from a geometrical perspective, based on the concept of confidence region, and we proposed an 'optimal' choice of the three time-points, in order to reduce the misclassification to a minimum. Comparing the original 3TP method with our proposal on the basis of misclassification rate, our results show that the modified 3TP method can lead to better performance. Preliminary results on real data have been also reported. Moreover, our proposal has a sounding mathematical basis and is easily generalisable to the case of more than two parameters and to other modalities such as DCE-CT. (C) 2014 Elsevier Ltd. All rights reserved
A comparison of fitting algorithms for diffusion-weighted MRI data analysis using an intravoxel incoherent motion model
No full textDCE-MRI: Lesion Detection and Classification in Breast Cancer
No full textDynamic contrast-enhanced MRI (DCE-MRI) is a well established, high-performance, imaging modality for the diagnosis and management of patients with solid tumors. In the last two decades, the diagnosis, grading and classification of tumours has considerably benefited from the development of DCE-MRI which is now essential for the adequate clinical management of many tumour types. The main aim of this work is to investigate the use of semi-quantitative and quantitative functional parameters for segmentation and classification of breast lesions via DCE-MRI. The objectives of the work can be detailed as follows: to review and describe the most diffused techniques for evaluating the time intensity curve in DCE-MRI with a focus on tracer kinetics models proposed in literature; to evaluate the influence of the parametrization of the classic bi-compartmental model; to assess the performance of simultaneous tracer kinetic modelling and pixel classification as either suspicious or not suspicious; to assess the performance of machine learning techniques using morphological, textural and dynamic features for segmentation and classification of breast lesions
Automated segmentation of comet assay images using Gaussian filtering and fuzzy clustering
No full textComet assay is one of the most popular tests for the detection of DNA damage at single cell level. In this study, an algorithm for comet assay analysis has been proposed, aiming to minimize user interaction and providing reproducible measurements. The algorithm comprises two-steps: (a) comet identification via Gaussian pre-filtering and morphological operators; (b) comet segmentation via fuzzy clustering. The algorithm has been evaluated using comet images from human leukocytes treated with a commonly used DNA damaging agent. A comparison of the proposed approach with a commercial system has been performed. Results show that fuzzy segmentation can increase overall sensitivity, giving benefits in bio-monitoring studies where weak genotoxic effects are expected
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