Multi-modal diffeomorphic demons registration based on point-wise mutual information

In this paper we propose a variational approach for multimodal image registration based on the diffeomorphic demons algorithm. Diffeomorphic demons has proven to be a robust and efficient way for intensity-based image registration. However, the main drawback is that it cannot deal with multiple modalities. We propose to replace the standard demons similarity metric (image intensity differences) by point-wise mutual information (PMI) in the energy function. By comparing the accuracy between our PMI based diffeomorphic demons and the B-Spline based free-form deformation approach (FFD) on simulated deformations, we show the proposed algorithm performs significantly better.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

A Hybrid Multimodal Non-Rigid Registration of MR Images Based on Diffeomorphic Demons

n this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Decision-making dysregulation in first-episode schizophrenia

Studies with chronic schizophrenia patients have demonstrated that patients fluctuate between rigid and unpredictable responses in decision-making situations, a phenomenon which has been called dysregulation. The aim of this study was to investigate whether schizophrenia patients already display dysregulated behavior at the beginning of their illness. Thirty-two first-episode schizophrenia or schizophreniform patients and 30 healthy controls performed the two-choice prediction task. The decision-making behavior of first-episode patients was shown to be characterized by a high degree of dysregulation accompanied by low metric entropy and a tendency towards increased mutual information. These results indicate that behavioral abnormalities during the two-choice prediction task are already present during the early stages of the illness.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Active Testing for Face Detection and Localization

We provide a novel search technique which uses a hierarchical model and a mutual information gain heuristic to efficiently prune the search space when localizing faces in images. We show exponential gains in computation over traditional sliding window approaches, while keeping similar performance levels.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

When left becomes right and vice versa: mirrored vision after cerebral hypoxia

The combination of acquired mirror writing and reading is an extremely rare neurological disorder. It is encountered when brain damaged patients prefer horizontally mirrored over normal script in writing and reading. Previous theories have related this pathology to a disinhibition of mirrored engrams in the non-dominant hemisphere, possibly accompanied by a reversal of the preferred scanning direction. Here, we report the experimental investigation of PR, a patient who developed pronounced mirror writing and reading following septic shock that caused hypoxic brain damage. A series of five oculomotor experiments revealed that the patient's preferred scanning direction was indeed reversed. However, PR showed striking scanpath abnormalities and mirror reversals that cannot be explained by previous theories. Considered together with mirror phenomena she displayed in neuropsychological tasks and everyday activities, our findings suggest a horizontal reversal of visual information on a perceptual level. In addition, a systematic manipulation of visual variables within two further experiments had dramatic effects on her mirror phenomena. When confronted with moving, flickering or briefly presented stimuli, PR showed hardly any left-right reversals. Not only do these findings underline the perceptual nature of her disorder, but also allow interpretation of the pathology in terms of a dissociation between visual subsystems. We speculate that early visual cortices are crucially involved in this dissociation. More generally, her mirrored vision may represent an extreme clinical manifestation of the relative instability of the horizontal axis in spatial vision.

Looking left with left neglect: the role of spatial attention when active vision selects local image features for fixation

When we actively explore the visual environment, our gaze preferentially selects regions characterized by high contrast and high density of edges, suggesting that the guidance of eye movements during visual exploration is driven to a significant degree by perceptual characteristics of a scene. Converging findings suggest that the selection of the visual target for the upcoming saccade critically depends on a covert shift of spatial attention. However, it is unclear whether attention selects the location of the next fixation uniquely on the basis of global scene structure or additionally on local perceptual information. To investigate the role of spatial attention in scene processing, we examined eye fixation patterns of patients with spatial neglect during unconstrained exploration of natural images and compared these to healthy and brain-injured control participants. We computed luminance, colour, contrast, and edge information contained in image patches surrounding each fixation and evaluated whether they differed from randomly selected image patches. At the global level, neglect patients showed the characteristic ipsilesional shift of the distribution of their fixations. At the local level, patients with neglect and control participants fixated image regions in ipsilesional space that were closely similar with respect to their local feature content. In contrast, when directing their gaze to contralesional (impaired) space neglect patients fixated regions of significantly higher local luminance and lower edge content than controls. These results suggest that intact spatial attention is necessary for the active sampling of local feature content during scene perception.

The STEREO/PLASTIC response to solar wind ions (Flight measurements and models)

The Plasma and Supra-Thermal Ion Composition (PLASTIC) instrument is one of four experiment packages on board of the two identical STEREO spacecraft A and B, which were successfully launched from Cape Canaveral on 26 October 2006. During the two years of the nominal STEREO mission, PLASTIC is providing us with the plasma characteristics of protons, alpha particles, and heavy ions. PLASTIC will also provide key diagnostic measurements in the form of the mass and charge state composition of heavy ions. Three measurements (E/qk, time of flight, ESSD) from the pulse height raw data are used to characterize the solar wind ions from the solar wind sector, and part of the suprathermal particles from the wide-angle partition with respect to mass, atomic number and charge state. In this paper, we present a new method for flight data analysis based on simulations of the PLASTIC response to solar wind ions. We present the response of the entrance system / energy analyzer in an analytical form. Based on stopping power theory, we use an analytical expression for the energy loss of the ions when they pass through a thin carbon foil. This allows us to model analytically the response of the time of flight mass spectrometer to solar wind ions. Thus we present a new version of the analytical response of the solid state detectors to solar wind ions. Various important parameters needed for our models were derived, based on calibration data and on the first flight measurements obtained from STEREO-A. We used information from each measured event that is registered in full resolution in the Pulse Height Analysis words and we derived a new algorithm for the analysis of both existing and future data sets of a similar nature which was tested and works well. This algorithm allows us to obtain, for each measured event, the mass, atomic number and charge state in the correct physical units. Finally, an important criterion was developed for filtering our Fe raw flight data set from the pulse height data without discriminating charge states.