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.

The link between visual exploration and neuronal activity: A multi-modal study combining eye tracking, functional magnetic resonance imaging and transcranial magnetic stimulation

In the present multi-modal study we aimed to investigate the role of visual exploration in relation to the neuronal activity and performance during visuospatial processing. To this end, event related functional magnetic resonance imaging er-fMRI was combined with simultaneous eye tracking recording and transcranial magnetic stimulation (TMS). Two groups of twenty healthy subjects each performed an angle discrimination task with different levels of difficulty during er-fMRI. The number of fixations as a measure of visual exploration effort was chosen to predict blood oxygen level-dependent (BOLD) signal changes using the general linear model (GLM). Without TMS, a positive linear relationship between the visual exploration effort and the BOLD signal was found in a bilateral fronto-parietal cortical network, indicating that these regions reflect the increased number of fixations and the higher brain activity due to higher task demands. Furthermore, the relationship found between the number of fixations and the performance demonstrates the relevance of visual exploration for visuospatial task solving. In the TMS group, offline theta bursts TMS (TBS) was applied over the right posterior parietal cortex (PPC) before the fMRI experiment started. Compared to controls, TBS led to a reduced correlation between visual exploration and BOLD signal change in regions of the fronto-parietal network of the right hemisphere, indicating a disruption of the network. In contrast, an increased correlation was found in regions of the left hemisphere, suggesting an intent to compensate functionality of the disturbed areas. TBS led to fewer fixations and faster response time while keeping accuracy at the same level, indicating that subjects explored more than actually needed.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Factor analysis of responses to thermal, electrical, and mechanical painful stimuli supports the importance of multi-modal pain assessment

During the last decade, a multi-modal approach has been established in human experimental pain research for assessing pain thresholds and responses to various experimental pain modalities. Studies have concluded that differences in responses to pain stimuli are mainly related to variation between individuals rather than variation in response to different stimulus modalities. In a factor analysis of 272 consecutive volunteers (137 men and 135 women) who underwent tests with different experimental pain modalities, it was determined whether responses to different pain modalities represent distinct individual uncorrelated dimensions of pain perception. Volunteers underwent single painful electrical stimulation, repeated painful electrical stimulation (temporal summation), test for reflex receptive field, pressure pain stimulation, heat pain stimulation, cold pain stimulation, and a cold pressor test (ice water test). Five distinct factors were found representing responses to 5 distinct experimental pain modalities: pressure, heat, cold, electrical stimulation, and reflex-receptive fields. Each of the factors explained approximately 8% to 35% of the observed variance, and the 5 factors cumulatively explained 94% of the variance. The correlation between the 5 factors was near null (median ρ=0.00, range -0.03 to 0.05), with 95% confidence intervals for pairwise correlations between 2 factors excluding any relevant correlation. Results were almost similar for analyses stratified according to gender and age. Responses to different experimental pain modalities represent different specific dimensions and should be assessed in combination in future pharmacological and clinical studies to represent the complexity of nociception and pain experience.