An extraction method of edge features from 3D laser point cloud based on corresponding images was proposed. After the registration of point cloud and corresponding image, the sub-pixel edge can be extracted from the image using gray moment algorithm. Then project the sub-pixel edge to the point cloud in fitting scan-lines. At last the edge features were achieved by linking the crossing points. The experimental results demonstrate that the method guarantees accurate fine extraction.
The aim of this study was to assess the validation of the local density random walk (LDRW) function to correct the delayed and dispersed arterial input function (AIF) data derived from dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). Instead of using the gamma-variate function to smooth and extrapolate the AIF curves, we suggested a method which was based on diffusion with drift approach. Forty-seven AIF curves from ten patients were segmented to test the effectiveness of the proposed method. The results of the comparisons with the gamma-variate function showed that the LDRW distribution function may provide a new means for more accurate correction of AIF curves.
This study presents a fast orthogonal search (FOS) method for modeling fMRI time series. Based on the system identification theory, an orthogonalization procedure to model the fMRI time series is described. FOS method does not require equally space data, and can resolve sinusoidal frequencies much more closely than Fourier transform method. After the time series are modeled by means of the FOS, F-test is employed to detect the activation regions. Eight volunteers' data were collected to validate the proposed method. The results demonstrate the feasibility of the proposed method.
Non-negative Matrix Factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. In this paper, we introduce this new technique to the field of fMRI data analysis. In order to make the representation suitable for task-related brain activation detection, we imposed some additional constraints, and defined an improved contrast function. We deduced the update rules and proved the convergence of the algorithm. In the procedure, the number of factors was determined by visual assessment. We studied 8 healthy right-handed adult volunteers by a 3.0T GE Signa scanner. A block design motor paradigm (bilateral finger tapping) stimulated the blood oxygenation level-dependent (BOLD) response. Gradient Echo EPI sequence was utilized to acquire BOLD contrast functional images. With this constrained NMF (cNMF) we could obtain major activation components and the corresponding time courses, which showed high correlation with the reference function (r>0.7). The results showed that our method would be feasible for detection brain activations from task-related fMRI series.
To study the technique and application of perfusion weighted imaging (PWI) in the diagnosis and medical treatment of acute stroke, 25 patients were examined by 1.5 T or 1.0 T MRI scanner. The Data analysis was done with "3D Med System" developed by our Lab to process the data and obtain apparent diffusion coefficient (ADC) map, cerebral blood volume (CBV) map, cerebral blood flow (CBF) map as well as mean transit time (MTT) map. In accute stage of stroke, normal or slightly hypointensity in T1-, hyperintensity in T2- and diffusion-weighted images were seen in the cerebral infarction areas. There were hypointensity in CBV map, CBF map and ADC map; and hyperintensity in MTT map that means this infarct area could be saved. If the hyperintensity area in MTT map was larger than the area in diffusion weighted imaging (DWI), the larger part was called penumbra and could be cured by an appropriate thrombolyitic or other therapy. The CBV, CBF and MTT maps are very important in the diagnosis and medical treatment of acute especially hyperacute stroke. Comparing with DWI, we can easily know the situation of penumbra and the effect of curvative therapy. Besides, we can also make a differential diagnosis with this method.