Diffusion tensor imaging (DTI) allows characterizing and exploiting diffusion anisotropy effects, thereby providing
important details about tissue microstructure. A major application in neuroimaging is the so-called fiber tracking where
neuronal connections between brain regions are determined non-invasively by DTI. Combining these neural pathways
within the human brain with the localization of activated brain areas provided by functional MRI offers important
information about functional connectivity of brain regions. However, DTI suffers from severe signal reduction due to the
diffusion-weighting. Ultra-high field (UHF) magnetic resonance imaging (MRI) should therefore be advantageous to
increase the intrinsic signal-to-noise ratio (SNR). This in turn enables to acquire high quality data with increased
resolution, which is beneficial for tracking more complex fiber structures. However, UHF MRI imposes some difficulties
mainly due to the larger B1 inhomogeneity compared to 3T MRI. We therefore optimized the parameters to perform DTI
at a 7 Tesla whole body MR scanner equipped with a high performance gradient system and a 32-channel head receive
coil. A Stesjkal Tanner spin-echo EPI sequence was used, to acquire 110 slices with an isotropic voxel-size of 1.2 mm
covering the whole brain. 60 diffusion directions were scanned which allows calculating the principal direction
components of the diffusion vector in each voxel. The results prove that DTI can be performed with high quality at UHF
and that it is possible to explore the SNT benefit of the higher field strength. Combining UHF fMRI data with UHF DTI
results will therefore be a major step towards better neuroimaging methods.
A major field in cognitive neuroscience investigates neuronal correlates of human decision-making processes [1, 2]. Is it
possible to predict a decision before it is actually revealed by the volunteer? In the presented manuscript we use a
standard paradigm from economic behavioral research that proved emotional influences on human decision making: the
Ultimatum Game (UG). In the UG, two players have the opportunity to split a sum of money. One player is deemed the
proposer and the other, the responder. The proposer makes an offer as to how this money should be split between the
two. The second player can either accept or reject this offer. If it is accepted, the money is split as proposed. If rejected,
then neither player receives anything.
In the presented study a real-time fMRI system was used to derive the brain activation of the responder. Using a
Relevance-Vector-Machine classifier it was possible to predict if the responder will accept or reject an offer. The
classification result was presented to the operator 1-2 seconds before the volunteer pressed a button to convey his
decision. The classification accuracy reached about 70% averaged over six subjects.
Functional MR imaging (fMRI) enables to detect different activated brain areas according to the performed
tasks. However, data are usually evaluated after the experiment, which prohibits intra-experiment optimization
or more sophisticated applications such as biofeedback experiments. Using a human-brain-interface (HBI), subjects
are able to communicate with external programs, e.g. to navigate through virtual scenes, or to experience
and modify their own brain activation. These applications require the real-time analysis and classification of
activated brain areas.
Our paper presents first results of different strategies for real-time pattern analysis and classification realized
within a flexible experiment control system that enables the volunteers to move through a 3D virtual scene in
real-time using finger tapping tasks, and alternatively only thought-based tasks.
KEYWORDS: Statistical analysis, Functional magnetic resonance imaging, Magnetic resonance imaging, Scanners, Optical spheres, Brain activation, Data acquisition, Hemodynamics, Visualization, Control systems
The real-time analysis of brain activation using functional MRI data offers a wide range of new experiments such
as investigating self-regulation or learning strategies. However, besides special data acquisition and real-time data
analysing techniques such examination requires dynamic and adaptive stimulus paradigms and self-optimising
MRI-sequences.
This paper presents an approach that enables the unified handling of parameters influencing the different software
systems involved in the acquisition and analysing process. By developing a custom-made Experiment Description
Language (EDL) this concept is used for a fast and flexible software environment which treats aspects like
extraction and analysis of activation as well as the modification of the stimulus presentation. We describe how
extracted real-time activation is subsequently evaluated by comparing activation patterns to previous acquired
templates representing activated regions of interest for different predefined conditions. According to those results
the stimulus presentation is adapted.
The results showed that the developed system in combination with EDL is able to reliably detect and evaluate
activation patterns in real-time. With a processing time for data analysis of about one second the approach is
only limited by the natural time course of the hemodynamic response function of the brain activation.
The monitoring of the development of cerebral diseases such as stroke or brain tumors with MRI requires high-precision comparison of initial and follow-up images. Retrospective registration often produces artifacts, especially at boundariesbetween different tissue structures. However, by manipulating the gradients, MRI scanners offer the possibility of shifting and rotating image planes fast and without removing the patient. Two approaches for prospective registration were implemented and tested on phantoms and healthy volunteers. To speed up calculation, both registration algorithms used the three orthogonal two-dimensional localizer images that were acquired prior to each measurement. In the first approach, the image is projected onto one axis to determine the rotation between initial and follow-up examination. The second algorithm uses cross-correlation for rotational correction. Both algorithms maximize the cross-correlation for correction of the shifts. After 2-D registration in each orientation, the gradients of the tomograph are adapted according to the calculated transformation matrix. The results were evaluated with a 3-D rigid-body registration using Automated Image Registration. The cross-correlation method was found to be very robust, while the 1-D projection algorithm was sufficiently fast but registration results depended on the shape of the head.
KEYWORDS: Magnetic resonance elastography, Brain, Signal attenuation, Tissues, Oscillators, Brain mapping, In vivo imaging, Convolution, Neuroimaging, Diffraction
A new method for evaluating Magnetic Resonance Elastography (MRE) wave images is introduced, which consists of both local frequency estimation (LFE) and simulation of wave patterns by a coupled harmonic oscillator (CHO) approach. It is shown that i) LFE performs improved reconstruction by use of Gauss filters and ii) CHO calculations can help to refine the resulting wave speed or elasticity map by taking local attenuation, reflection, and diffraction into account. The performance of new LFE and CHO calculations is demonstrated by MRE experiments on a gel phantom as well as by simulations of shear waves in a brain phantom, such as for potential in-vivo MRE-experiments.
Diffusion- and perfusion-weighted magnetic resonance imaging (DWI, PWI) allows the diagnosis of ischemic brain injury at a time when ischemic lesions may not yet be detectable in computer tomography or T2-weighted (T2w) MRI. However, regions with pathologic apparent diffusion coefficients (ADC) do not necessarily match with regions of prolonged mean transit times (MTT) or pathologic relative cerebral blood flow (rCBF). Mismatching parts are thought to correlate with tissues that can be saved by appropriate treatment. Ten patients with cerebral ischemia underwent standard T1w and T2w imaging as well as single-shot echo planar imaging (EPI) DWI, and PWI. Multidimensional histograms were constructed from T2w images, DWI, ADC, rCBF, and MTT maps. After segmenting different tissues, signal changes of ischemic tissues relative to unaffected parenchyma were calculated. Combining different information allowed the segmentation of lesions and unaffected tissues. Acute infarcts exhibited decreased ADC values as well as hypo- and hyperperfused areas. Correlating ADC, T2w, and rCBF with clinical symptoms allowed the estimation of age and perfusion state of the lesions. Combining DWI, PWI, and standard imaging overcomes strongly fluctuating parameters such as ADC values. A multidimensional parameter-set characterizes unaffected and pathologic tissues which may help in the evaluation of new therapeutic strategies.
A histogram-based segmentation technique was extended to exploit information acquired by manifold MRI techniques. An automated method was used to combine T2-weighted imaging, diffusion-weighted imaging (DWI), and derived maps of the quantitative apparent diffusion coefficient (ADC). DWI allows the early detection of cerebral ischemia, and the calculated ADC value may provide information on pathophysiologic changes. Different optionally shaped clusters were characterized as separate local density maxima in the resultant 3D histogram. Cluster borders were determined by detecting density minima. Distinct but related clusters could be merged in the histogram using the Euclidian distance and a score describing the spatial neighborhood of pixels in the image. In healthy volunteers, gray matter, white matter, muscle, skin, adipose tissue, and cerebrospinal fluid were clearly identified by the automated analysis. In stroke patients, ischemic regions were reliably segmented irrespective of shape, size, and location. The time course of relative ADC changes in ischemic lesions was determined. Results were confirmed by a radiologist. The proposed automatic segmentation algorithm can be used without restrictions for the fast analysis of any multidimensional dataset. The method has proved to be reliable for determining quantities containing information on the physiologic state of tissue, such as the ADC.
KEYWORDS: Computer security, Magnetic resonance imaging, Image segmentation, Network security, Image encryption, Data communications, Diffusion, Tissues, Image processing, Chemical elements
To ensure the acceptance of telemedical applications several obstacles must be overcome: the transfer of huge amounts of data over heterogeneous hard- and software platforms must be optimized; extended data post-processing is often required; and data security must be taken into consideration; post- processing based on secured data exchange must retain the relationship between original and post-processed images. To analyze and solve these problems, applications of distributed medical services were integrated. Data transfer and management was based on the Digital Imaging and Communications (DICOM) standard. To account for platform- independence of remote users, a novel DICOM server and viewer as implemented in JAVA. Different DICOM-conform data security concepts were analyzed. Encryption of the complete data stream using secure socket layers as well as a partial encryption concepts were tested. The best result was attained by a DICOM-conform encryption of patient-relevant data. The implementation medical services, which used newly develop techniques of magnetic resonance imaging, allowed a much earlier diagnosis of the human brain infarct. The integrated data security enabled remote segmentation within the unsecured internet, followed by storing the data back into the secured network.
The system presented here enhances documentation and data- secured, second-opinion facilities by integrating video sequences into DICOM 3.0. We present an implementation for a medical video server extended by a DICOM interface. Security mechanisms conforming with DICOM are integrated to enable secure internet access. Digital video documents of diagnostic and therapeutic procedures should be examined regarding the clip length and size necessary for second opinion and manageable with today's hardware. Image sources relevant for this paper include 3D laparoscope, 3D surgical microscope, 3D open surgery camera, synthetic video, and monoscopic endoscopes, etc. The global DICOM video concept and three special workplaces of distinct applications are described. Additionally, an approach is presented to analyze the motion of the endoscopic camera for future automatic video-cutting. Digital stereoscopic video sequences are especially in demand for surgery . Therefore DSVS are also integrated into the DICOM video concept. Results are presented describing the suitability of stereoscopic display techniques for the operating room.
The system presented here enhances documentation and data- secured, second-opinion facilities by integrating video into DICOM3.0. Digital stereoscopic video sequences (DSVS) are especially in demand for surgery (laparoscopy, microsurgery, surgical microscopy, second opinion, virtual reality). Therefore DSVS are also integrated into the DICOM video concept. We present an implementation for a medical video server extended by a DICOM interface. Security mechanisms conforming with DICOM are integrated to enable secure internet access. Digital (stereoscopic) video sequences relevant for surgery should be examined regarding the clip length necessary for diagnosis and documentation and the clip size manageable with today's hardware. Methods for DSVS compression are described, implemented, and tested. Image sources relevant for this paper include, among others, a stereoscopic laparoscope and a monoscopic endoscope. Additionally, an approach is presented to analyze the motion of the endoscopic camera for future automatic video- cutting.
KEYWORDS: Computer security, Image encryption, Network security, Solid state lighting, Data storage, Data communications, Internet, Magnetic resonance imaging, Standards development, Picture Archiving and Communication System
Local area networks in hospitals with connection to the Internet enable remote access to medical data and the deployment of distributed medical services. The use of standardized protocols like DICOM as required by the heterogeneous hard- and software infrastructure aggravates the problem that intruders can potentially gain access to sensitive data. Different levels of data protection are therefore required depending on the utilization of secured or publicly accessible networks, the use of standardized communication, and the differing national data security regulations. To investigate different speed-optimized data security concepts, we constructed exemplary scenarios with distributed telemedical services utilizing DICOM-conform software systems. The hospital networks are separated from the Internet by firewalls. Communication between the DICOM applications was made possible by integrating a security level between the DICOM upper layer protocol and the TCP/IP interface, while encrypting the whole datastream using the Secure Socket Layer Protocol (SSL). A DICOM-conform encryption of selected parts of the DICOM messages and files was developed, that encodes only patient-relevant data. Additionally a security proposal of the DICOM working group on security was implemented and analyzed. Data were encrypted by using either symmetric (public and private key) or symmetric (secret key) methods. This sped up the overall data transfer rate and allowed the DICOM-conform, off-line data storage.
Telemedical services rely on the digital transfer of large amounts of data in a short time. The acceptance of these services requires therefore new hard- and software concepts. The fast exchange of data is well performed within a high- speed ATM-based network. The fast access to the data from different platforms imposes more difficult problems, which may be divided into those relating to standardized data formats and those relating to different levels of data security across nations. For a standardized access to the formats and those relating to different levels of data security across nations. For a standardized access to the image data, a DICOM 3.0 server was implemented.IMages were converted into the DICOM 3.0 standard if necessary. The access to the server is provided by an implementation of DICOM in JAVA allowing access to the data from different platforms. Data protection measures to ensure the secure transfer of sensitive patient data are not yet solved within the DICOM concept. We investigated different schemes to protect data using the DICOM/JAVA modality with as little impact on data transfer speed as possible.
Images with a low signal-to-noise ratio (SNR) were processed with different algorithms based on the anisotropic diffusion (AD). This algorithm reduces the noise while preserving or enhancing the edges. Since sequences provide more image information, we developed an extension of the AD. In the modified AD the diffusion coefficients are used to vary the contrast normalization of successive frames. The Chamfer distance was used to measure the displacement of edges between the original and the processed images. Phantom images with varying gray levels and SNR, with fluctuating borders and with gross distortions were tested, as were clinical ultrasound images of the abdomen. The feed forward anisotropic diffusion (FFAD) scheme showed improved edge preserving capability for the phantom images as compared to the AD for the phantom images. Transferring the image information stabilized the edge detection even in cases where gross distortions or fluctuating contrast due to overall signal intensity changes led to geometric shifts in AD. Applying the FFAD to ultrasound images, the differences were less pronounced partly because of the different noise behavior.
Keywords: Noise reduction, image-sequence processing, anisotropic diffusion, edge detection
KEYWORDS: Visualization, Near infrared spectroscopy, Blood, Magnetic resonance imaging, Signal attenuation, Signal detection, Hemodynamics, Functional magnetic resonance imaging, Tissue optics, Chromophores
We examined local changes of cerebral oxygenation in response to visual stimuli by means of near infrared
spectroscopy. A sharply outlined colored moving stimulus which is expected to evoke a broad activation of the striate and prestriate cortex was presented to sixteen healthy subjects. Six of these subjects were also exposed to a colored stationary and a gray stationary stimulus. In two subjects the colored moving stimulus was tested against the colored stationary with an optode position presumably over area V5/MT. As a control condition, subjects performed a simple finger opposition task. Since the calcarine fissure varies greatly with respect to bony landmarks, optodes were positioned individually according to 3-D reconstructed magnetic resonance imaging (MRI). Concentration changes in oxyhemoglobin ([oxy-Hb]) and deoxyhemoglobin ([deoxy-Hb]) were continuously monitored with a temporal resolution of 1 s, using an NIRO 500 (Hamamatsu Photonics, KK, Japan). In response to the visual stimulus, the grand average across all sixteen subjects resulted
in a significant increase in [oxy-Hb] of 0.3360.09 arbitrary units (mean6S.E.M.) mirrored by a significant decrease in [deoxy-Hb] of −0.1860.02 arbitrary units, while the motor control condition elicited no significant changes in any parameters. When the near infrared spectroscopy probes were positioned over area V5/MT, the drop of [deoxy-Hb] associated with the moving stimulus was significantly more pronounced than with the stationary stimulus in both subjects examined. No significant differences between the visual stimuli were observed at the optode position close to the calcarine fissure. The oxygenation changes observed in this study are consistent with the pattern we have reported for motor activation. They are in line with physiological considerations and functional MRI studies relying on blood oxygenation level-dependent contrast.
KEYWORDS: Computer security, Network security, 3D modeling, Databases, Tissues, Software development, Local area networks, Brain, Data transmission, Standards development
The ATM-based Metropolitan Area Network (MAN) of Berlin connects two university hospitals (Benjamin Franklin University Hospital and Charite) with the computer resources of the Technical University of Berlin (TUB). Distributed new medical services have been implemented and will be evaluated within the highspeed MAN of Berlin. The network with its data transmission rates of up to 155 Mbit/s renders these medical services externally available to practicing physicians. Resource and application sharing is demonstrated by the use of two software systems. The first software system is an interactive 3D reconstruction tool (3D- Medbild), based on a client-server mechanism. This structure allows the use of high- performance computers at the TUB from the low-level workstations in the hospitals. A second software system, RAMSES, utilizes a tissue database of Magnetic Resonance Images. For the remote control of the software, the developed applications use standards such as DICOM 3.0 and features of the World Wide Web. Data security concepts are being tested and integrated for the needs of the sensitive medical data. The highspeed network is the necessary prerequisite for the clinical evaluation of data in a joint teleconference. The transmission of digitized real-time sequences such as video and ultrasound and the interactive manipulation of data are made possible by Multi Media tools.
A tissue database was established by using multidimensional clusters of exact longitudinal (T1) and transversal (T2) relaxation times and spin density, allowing the automatic segmentation and characterization of healthy and pathologic tissue. All parameters were simultaneously acquired employing a modified Multi-Echo pulse sequence. Initial clinical results showed a good differentiation between normal brain tissue and pathologic tissue like edema and meningioma. Inhomogeneous tumors such as high-grade glioblastoma were difficult to characterize automatically. The implementation of a diffusion-weighted modified Tanner-Stejskal pulse sequence allows the acquisition of the Apparent Diffusion Constant (ADC), which has been incorporated for the first time into a multidimensional information set as a new tissue-characterizing parameter. This parameter is sensitive to changes in the mobility of water in and between different cell compartments resulting from metabolic cell disorders like ischemic or edematous processes. To reproduce the known results of animal experiments, where as early as 30 min after an ischemic event the measurement of the ADC led to a diagnosis, diffusion-weighted imaging had to be implemented on a standard clinical scanner. The correction of unavoidable motion artifacts, which occur when applying diffusion- weighted spin echo sequences on standard clinical scanners, require the implementation of a special sequence using the navigator echo method followed by a correction algorithm of the raw data in Fourier space. Initial results showed a significant improvement in the differentiation of healthy and pathologic tissue classes.
A time resolved fluorescence spectroscopic technique was employed for identification purposes of endogen molecules based on their individual decay characteristics. For the first time also relative concentrations of mixtures could be determined just from the knowledge of the fluorescence signals only. The results agree well with the expected concentrations values.
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