Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.

Validation of tissue modelization and classification techniques in T1-weighted MR brain images

We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

Automatic quality assessment in structural brain magnetic resonance imaging

MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.

The geometric structure of the brain fiber pathways.

The structure of the brain as a product of morphogenesis is difficult to reconcile with the observed complexity of cerebral connectivity. We therefore analyzed relationships of adjacency and crossing between cerebral fiber pathways in four nonhuman primate species and in humans by using diffusion magnetic resonance imaging. The cerebral fiber pathways formed a rectilinear three-dimensional grid continuous with the three principal axes of development. Cortico-cortical pathways formed parallel sheets of interwoven paths in the longitudinal and medio-lateral axes, in which major pathways were local condensations. Cross-species homology was strong and showed emergence of complex gyral connectivity by continuous elaboration of this grid structure. This architecture naturally supports functional spatio-temporal coherence, developmental path-finding, and incremental rewiring with correlated adaptation of structure and function in cerebral plasticity and evolution.

Cross validation of experts versus registration methods for target localization in deep brain stimulation.

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Conserved developmental expression of Fezf in chordates and Drosophila and the origin of the Zona Limitans Intrathalamica (ZLI) brain organizer

Background: The zona limitans intrathalamica (ZLI) and the isthmus organizer (IsO) are two major secondary organizers of vertebrate brain development. These organizers are located at the interface of the expression domains of key patterning genes (Fezf-Irx and Otx-Gbx, respectively). To gain insights into the evolutionary origin of the ZLI, we studied Fezf in bilaterians. Results: In this paper, we identified a conserved sequence motif (Fezf box) in all bilaterians. We report the expression pattern of Fezf in amphioxus and Drosophila and compare it with those of Gbx, Otx and Irx. We found that the relative expression patterns of these genes in vertebrates are fully conserved in amphioxus and flies, indicating that the genetic subdivisions defining the location of both secondary organizers in early vertebrate brain development were probably present in the last common ancestor of extant bilaterians. However, in contrast to vertebrates, we found that Irx-defective flies do not show an affected Fezf expression pattern. Conclusions: The absence of expression of the corresponding morphogens from cells at these conserved genetic boundaries in invertebrates suggests that the organizing properties might have evolved specifically in the vertebrate lineage by the recruitment of key morphogens to these conserved genetic locations.

Conserved developmental expression of Fezf in chordates and Drosophila and the origin of the Zona Limitans Intrathalamica (ZLI) brain organizer

Background: The zona limitans intrathalamica (ZLI) and the isthmus organizer (IsO) are two major secondary organizers of vertebrate brain development. These organizers are located at the interface of the expression domains of key patterning genes (Fezf-Irx and Otx-Gbx, respectively). To gain insights into the evolutionary origin of the ZLI, we studied Fezf in bilaterians. Results: In this paper, we identified a conserved sequence motif (Fezf box) in all bilaterians. We report the expression pattern of Fezf in amphioxus and Drosophila and compare it with those of Gbx, Otx and Irx. We found that the relative expression patterns of these genes in vertebrates are fully conserved in amphioxus and flies, indicating that the genetic subdivisions defining the location of both secondary organizers in early vertebrate brain development were probably present in the last common ancestor of extant bilaterians. However, in contrast to vertebrates, we found that Irx-defective flies do not show an affected Fezf expression pattern. Conclusions: The absence of expression of the corresponding morphogens from cells at these conserved genetic boundaries in invertebrates suggests that the organizing properties might have evolved specifically in the vertebrate lineage by the recruitment of key morphogens to these conserved genetic locations.

Interface Implementation for GPRS/PCU Software Testing with Emulators

Jatkuvasti lisääntyvä matkapuhelinten käyttäjien määrä, internetin kehittyminen yleiseksi tiedon ja viihteen lähteeksi on luonut tarpeen palvelulle liikkuvan työaseman liittämiseksi tietokoneverkkoihin. GPRS on uusi teknologia, joka tarjoaa olemassa olevia matka- puhelinverkkoja (esim. NMT ja GSM) nopeamman, tehokkaamman ja taloudellisemman liitynnän pakettidataverkkoihin, kuten internettiin ja intranetteihin. Tämän työn tavoitteena oli toteuttaa GPRS:n paketinohjausyksikön (Packet Control Unit, PCU) testauksessa tarvittavat viestintäajurit työasemaympristöön. Aidot matkapuhelinverkot ovat liian kalliita, eikä niistä saa tarvittavasti lokitulostuksia, jotta niitä voisi käyttää GPRS:n testauksessa ohjelmiston kehityksen alkuvaihessa. Tämän takia PCU-ohjelmiston testaus suoritetaan joustavammassa ja helpommin hallittavassa ympäristössä, joka ei aseta kovia reaaliaikavaatimuksia. Uusi toimintaympäristö ja yhteysmedia vaativat PCU:n ja muiden GPRS-verkon yksiköiden välisistä yhteyksistä huolehtivien ohjelman osien, viestintäajurien uuden toteutuksen. Tämän työn tuloksena syntyivät tarvittavien viestintäajurien työasemaversiot. Työssä tarkastellaan eri tiedonsiirtotapoja ja -protokollia testattavan ohjelmiston vaateiden, toteutetun ajurin ja testauksen kannalta. Työssä esitellään kunkin ajurin toteuttama rajapinta ja toteutuksen aste, eli mitkä toiminnot on toteutettu ja mitä on jätetty pois. Ajureiden rakenne ja toiminta selvitetään siltä osin, kuin se on oleellista ohjelman toiminnan kannalta.