An adaptive template-matching method and its application to the boundary detection of brachial artery ultrasound scans.

We developed an adaptive template-matching method for vessel wall boundary detection in brachial artery ultrasound (US) scans. The computer-aided identification of lumen-intima and media-adventitia boundaries of the brachial artery US scan is a critical step for flow-mediated vasodilator response measurement, which has become an increasingly important tool in both clinical and research applications. The adaptive template we propose in this paper is a combination of two parameterized Gaussian envelopes that approximates the US pulse envelope. The algorithm for template matching is cast as a constrained nonlinear least squares problem. A best match between the template and the observed US scan line signal results in a set of optimum parameters of the adaptive template, and the location of the boundaries is directly computed from these parameters. We present the results of applying our method to synthetic and clinical data, showing that the adaptive template-matching method provides superior accuracy in detecting the media-adventitia boundaries of both the near wall and the far wall of the vessel to that of conventional edge-detection methods.

Ultrasound measurement of brachial flow-mediated vasodilator response.

Brachial artery flow-mediated vasodilation is increasingly used as a measure of endothelial function. High resolution ultrasound provides a noninvasive method to observe this flow-mediated vasodilation by monitoring the diameter of the artery over time following a transient flow stimulus. Since hundreds of ultrasound images are required to continuously monitor brachial diameter for the 2-3 min during which the vasodilator response occurs, an automated diameter estimation is desirable. However, vascular ultrasound images suffer from structural noise caused by the constructive and destructive interference of the backscattered signals, and the true boundaries of interest that define the diameter are frequently obscured by the multiple-layer structure of the vessel wall. These problems make automated diameter estimation strategies based on the detection of the vessel wall boundary difficult. We obtain a robust automated measurement of the vasodilator response by automatically locating the artery using a variable window method, which gives both the lumen center and width. The vessel wall boundary is detected by a global constraint deformable model, which is insensitive to the structural noise in the boundary area. The ambiguity between the desired boundary and other undesired boundaries is resolved by a spatiotemporal strategy. Our method provides excellent reproducibility both for interreader and intrareader analyzes of percent change in diameter, and has been successfully used in analyzing over 4000 brachial flow-mediated vasodilation scans from several medical centers in the United States.

Co-registration of cortical magnetic stimulation and functional magnetic resonance imaging.

Functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) are noninvasive techniques recently used to investigate cortical motor physiology. However, these modalities measure different phenomena, and in studies of human motor control they have given inconsistent results. We have developed a reproducible technique which co-registers TMS and fMRI, using a frameless method. In four normal subjects, the TMS map and fMRI activation were present on the primary motor cortex contralateral to the target hand, with some extension into primary sensory cortex. fMRI activation alone was also present in the medial motor cortex bilaterally and in the sensorimotor cortex ipsilateral to the target hand. This technique allows a more comprehensive evaluation of the physiologic events involved in motor control.

Performance evaluation of filtered backprojection reconstruction and iterative reconstruction methods for PET images.

The filtered backprojection (FBP) algorithm and statistical model based iterative algorithms such as the maximum likelihood (ML) reconstruction or the maximum a posteriori (MAP) reconstruction are the two major classes of tomographic reconstruction methods. The FBP method is widely used in clinical setting while iterative methods have attracted research interests in the past decade. In this paper we studied the performance of the FBP, the ML and the MAP methods using simulated projection data. The experiment showed that the MAP algorithm generated superior image quality in terms of the bias, the variance, and the average mean squared error (MSE) measures.

Statistical models of partial volume effect.

Statistical models of partial volume effect for systems with various types of noise or pixel value distributions are developed and probability density functions are derived. The models assume either Gaussian system sampling noise or intrinsic material variances with Gaussian or Poisson statistics. In particular, a material can be viewed as having a distinct value that has been corrupted by additive noise either before or after partial volume mixing, or the material could have nondistinct values with a Poisson distribution as might be the case in nuclear medicine images. General forms of the probability density functions are presented for the N material cases and particular forms for two- and three-material cases are derived. These models are incorporated into finite mixture densities in order to more accurately model the distribution of image pixel values. Examples are presented using simulated histograms to demonstrate the efficacy of the models for quantification. Modeling of partial volume effect is shown to be useful when one of the materials is present in images mainly as a pixel component.

Effects of intravoxel velocity distributions on the accuracy of the phase-mapping method in phase-contrast MR angiography.

The phase-mapping method of phase-contrast magnetic resonance angiography is shown to be based on an implicit assumption that the intravoxel velocity distribution is symmetric about its mean velocity. The effect of asymmetric distributions on the accuracy of quantitative average velocity measurements is determined analytically and verified experimentally. An explicit formulation is developed for the estimated average velocity in a voxel as a function of the true average velocity and the asymmetry of the distribution about the true average velocity. Worst-case distributions are determined for unidirectional and bidirectional flow, and the special case of laminar flow is also investigated. Computer simulations and phantom imaging experiments demonstrate the accuracy of the analysis. For voxels with unidirectional flow, the phase-mapping method produces accurate estimates of average velocity, while results for bidirectional flow indicate possible large errors unless the aliasing velocity is increased, which decreases the signal-to-noise ratio in the resultant velocity map image.

Quantification of MR brain images by mixture density and partial volume modeling.

The problem of automatic quantification of brain tissue by utilizing single-valued (single echo) magnetic resonance imaging (MRI) brain scans is addressed. It is shown that this problem can be solved without classification or segmentation, a method that may be particularly useful in quantifying white matter lesions where the range of values associated with the lesions and the white matter may heavily overlap. The general technique utilizes a statistical model of the noise and partial volume effect together with a finite mixture density description of the tissues. The quantification is then formulated as a minimization problem of high order with up to six separate densities as part of the mixture. This problem is solved by tree annealing with and without partial volume utilized, the results compared, and the sensitivity of the tree annealing algorithm to various parameters is exhibited. The actual quantification is performed by two methods: a classification-based method called Bayes quantification, and parameter estimation. Results from each method are presented for synthetic and actual data.

Evaluation of a new magnetic resonance imaging method for quantitating adipose tissue areas.

We have developed a new magnetic resonance imaging (MRI) protocol to quantitate intraabdominal and subcutaneous fat and have validated it by comparing measurements of fat areas by MRI with those obtained by computed tomography (CT) in 11 asymptomatic volunteers who all had a single CT and MRI image taken at the level of the umbilicus. The new MRI protocol was based on a water-fat separation method by which the slice selection routines excite water and fat protons in different positions along the slice select direction. This method performed more reliably than earlier methods based on phase differences between water and fat signals. Fat areas measured by MRI exceeded those measured by CT by 8-22 percent, and fat areas and ratios obtained by MRI correlated well with CT (r = 0.98 for areas and, for ratios, r = 0.81). The ratio of intraabdominal/subcutaneous fat measured by MRI in seven males was significantly greater than that in four females. We also compared the new method with a previously published inversion recovery (IR) method in seven additional volunteers. Agreement between the two methods was excellent, and the major differences were technical: the IR protocol produced images that may require custom image processing programs when obtained on some scanners. Comparability of the two methods provides further reassurance of the validity of both. MRI presents an attractive opportunity for directly measuring intraabdominal fat in order to correlate this with metabolic parameters and to visualize changes during weight loss.

Quantization improvement in MRI using dual quantizers.

The quantization of magnetic resonance imaging (MRI) data can cause information loss due to quantizer/data mismatch. The authors address a method for improved quantization as well as techniques for measuring the improvement in such methods. A dual quantizer scheme is described and simulated which is fast and more accurately quantizes MRI data than conventional methods. The approach is to use two quantizers, one for the high-level data and one for the low-level data. This adaptive, dual quantization scheme is simple and provides significant improvements in image quality, especially for three-dimensional (3-D) acquisition. Results are given which show how well the low frequencies are represented and indicate the increased fidelity of the high-frequency components. These results show a significant improvement in signal-to-noise ratio as well as in detection tasks for both noiseless data and data which include varying amounts of system noise.

Adipose tissue determinations in cadavers--a comparison between cross-sectional planimetry and computed tomography.

The adipose tissue surfaces in 11 slices (+/- 5 cm from the umbilicus) were compared in two cadavers using computed tomography (CT) versus planimetry of band-sawed slices of the corresponding sections. A very close correlation was found with partial correlations of around 0.90. Retroperitoneal fat formed a considerable proportion of the total adipose tissue surface in the slices. The results were similar whether fat was defined as -250 to -50, -190 to -30, or -140 to -40 Hounsfield units. These data indicate that CT measurements agree closely with a direct morphometric method and thus can be used as a 'gold standard' for future development. The fact that fat which is located extraperitoneally, but still intraabdominally, constitutes a significant proportion of the slice surface in the umbilical region indicates that data relating intraabdominal fat measurements to metabolic functions must be interpreted with caution.