59 research outputs found
Microtesla MRI of the human brain combined with MEG
One of the challenges in functional brain imaging is integration of
complementary imaging modalities, such as magnetoencephalography (MEG) and
functional magnetic resonance imaging (fMRI). MEG, which uses highly sensitive
superconducting quantum interference devices (SQUIDs) to directly measure
magnetic fields of neuronal currents, cannot be combined with conventional
high-field MRI in a single instrument. Indirect matching of MEG and MRI data
leads to significant co-registration errors. A recently proposed imaging method
- SQUID-based microtesla MRI - can be naturally combined with MEG in the same
system to directly provide structural maps for MEG-localized sources. It
enables easy and accurate integration of MEG and MRI/fMRI, because microtesla
MR images can be precisely matched to structural images provided by high-field
MRI and other techniques. Here we report the first images of the human brain by
microtesla MRI, together with auditory MEG (functional) data, recorded using
the same seven-channel SQUID system during the same imaging session. The images
were acquired at 46 microtesla measurement field with pre-polarization at 30
mT. We also estimated transverse relaxation times for different tissues at
microtesla fields. Our results demonstrate feasibility and potential of human
brain imaging by microtesla MRI. They also show that two new types of imaging
equipment - low-cost systems for anatomical MRI of the human brain at
microtesla fields, and more advanced instruments for combined functional (MEG)
and structural (microtesla MRI) brain imaging - are practical.Comment: 8 pages, 5 figures - accepted by JM
從中文作文看學生的情意表達能力: 個案研究
本文是一個追蹤研究,首先收集研究對象中一至中三的作文103篇,並採用現象學研究法(Phenomenological
Research )的意念進行研究。現象學研究法的重點在於深入了解人類自然的生活,把沒有虛飾的生活體驗和意義呈現出來。本文主要運用兩種分析工具:威堅遜模式(Wilkinson, 1980)及內容分析(text analysis)。論文研究的目的:分析受試者初中情意表達能力的層次。
This article is a longitudinal research which monitors 103 essays of a student from F.1 to F.3 by adopting 'phenomenological research'. Phenomenological research is based on the deep understanding of human life, presenting us with the truest life experiences without disguise. The ability to express emotion of a student as reflected from his Chinese composition. Two models are employed in this research: Wilkinson’s (1980) and text analysis. The objectives of this research is to analyse the abilities of junior secondary school students to express emotions.link_to_OA_fulltex
Quantitative measurement of the vibrational amplitude and phase in photorefractive time-average interferometry: A comparison with electronic speckle pattern interferometry
A method for dynamic subtraction MR imaging of the liver
BACKGROUND: Subtraction of Dynamic Contrast-Enhanced 3D Magnetic Resonance (DCE-MR) volumes can result in images that depict and accurately characterize a variety of liver lesions. However, the diagnostic utility of subtraction images depends on the extent of co-registration between non-enhanced and enhanced volumes. Movement of liver structures during acquisition must be corrected prior to subtraction. Currently available methods are computer intensive. We report a new method for the dynamic subtraction of MR liver images that does not require excessive computer time. METHODS: Nineteen consecutive patients (median age 45 years; range 37–67) were evaluated by VIBE T1-weighted sequences (TR 5.2 ms, TE 2.6 ms, flip angle 20°, slice thickness 1.5 mm) acquired before and 45s after contrast injection. Acquisition parameters were optimized for best portal system enhancement. Pre and post-contrast liver volumes were realigned using our 3D registration method which combines: (a) rigid 3D translation using maximization of normalized mutual information (NMI), and (b) fast 2D non-rigid registration which employs a complex discrete wavelet transform algorithm to maximize pixel phase correlation and perform multiresolution analysis. Registration performance was assessed quantitatively by NMI. RESULTS: The new registration procedure was able to realign liver structures in all 19 patients. NMI increased by about 8% after rigid registration (native vs. rigid registration 0.073 ± 0.031 vs. 0.078 ± 0.031, n.s., paired t-test) and by a further 23% (0.096 ± 0.035 vs. 0.078 ± 0.031, p < 0.001, paired t-test) after non-rigid realignment. The overall average NMI increase was 31%. CONCLUSION: This new method for realigning dynamic contrast-enhanced 3D MR volumes of liver leads to subtraction images that enhance diagnostic possibilities for liver lesions
Educational programs for imaging physicists should emphasize the science of imaging rather than the technology of imaging
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135393/1/mp2235.pd
Tissue classification of noisy mr brain images using constrained gmm
Abstract. We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of Gaussians, with each brain tissue represented by a large number of the Gaussian components in order to capture the complex tissue spatial layout. The intensity of a tissue is considered a global feature and is incorporated into the model through parameter tying of all the related Gaussians. The EM algorithm is utilized to learn the parameter-tied Gaussian mixture model. A new initialization method is applied to guarantee the convergence of the EM algorithm to the global maximum likelihood. Segmentation of the brain image is achieved by the affiliation of each voxel to a selected tissue class. The presented algorithm is used to segment 3D, T1–weighted, simulated and real MR images of the brain into three different tissues, under varying noise conditions. Quantitative results are presented and compared with state–of–the–art results reported in the literature.
Simultaneous magnetoencephalography and SQUID detected nuclear MR in microtesla magnetic fields
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