Spatial Normalization Research Articles

Using Perfusion Contrast for Spatial Normalization of ASL MRI Images in a Pediatric Craniosynostosis Population.

Spatial normalization is an important step for group image processing and evaluation of mean brain perfusion in anatomical regions using arterial spin labeling (ASL) MRI and is typically performed via high-resolution structural brain scans. However, structural segmentation and/or spatial normalization to standard space is complicated when gray-white matter contrast in structural images is low due to ongoing myelination in newborns and infants. This problem is of particularly clinical relevance for imaging infants with inborn or acquired disorders that impair normal brain development. We investigated whether the ASL MRI perfusion contrast is a viable alternative for spatial normalization, using a pseudo-continuous ASL acquired using a 1.5 T MRI unit (GE Healthcare). Four approaches have been compared: (1) using the structural image contrast, or perfusion contrast with (2) rigid, (3) affine, and (4) nonlinear transformations – in 16 healthy controls [median age 0.83 years, inter-quartile range (IQR) ± 0.56] and 36 trigonocephaly patients (median age 0.50 years, IQR ± 0.30) – a non-syndromic type of craniosynostosis. Performance was compared quantitatively using the real-valued Tanimoto coefficient (TC), visually by three blinded readers, and eventually by the impact on regional cerebral blood flow (CBF) values. For both patients and controls, nonlinear registration using perfusion contrast showed the highest TC, at 17.51 (CI 6.66–49.38) times more likely to have a higher rating and 17.45–18.88 ml/100 g/min higher CBF compared with the standard normalization. Using perfusion-based contrast improved spatial normalization compared with the use of structural images, significantly affected the regional CBF, and may open up new possibilities for future large pediatric ASL brain studies.

Real-time spatial normalization for dynamic gesture classification

Real-time spatial normalization for dynamic gesture classification

Improved normalization of lesioned brains via cohort-specific templates.

In MRI studies, spatial normalization is required to infer results at the group level. In the presence of a brain lesion, such as in stroke patients, the normalization process can be affected by tissue loss, spatial deformations, signal intensity changes, and other stroke sequelae that introduce confounds into the group analysis results. Previously, most neuroimaging studies with lesioned brains have used normalization methods optimized for intact brains, raising potential concerns about the accuracy of the resulting transformations and, in turn, their reported group level results. In this study, we demonstrate the benefits of creating an intermediate, cohort‐specific template in conjunction with diffeomorphism‐based methods to normalize structural MRI images in stroke patients. We show that including this cohort‐specific template improves accuracy compared to standard methods for normalizing lesioned brains. Critically, this method reduces overall differences in normalization accuracy between stroke patients and healthy controls, and may improve the localization and connectivity of BOLD signal in functional neuroimaging data.

Effect of white matter hyperintensity on dopamine transporter availability of striatum measured by F-18 FP-CIT PET.

We aimed to evaluate the white matter hyperintensity (WMH) effect on dopamine transporter availability (DAT) of striatum. A total of 48 patients who showed visually normal F-18 FP-CIT uptake were included in this study. Each FP-CIT image were pre-processed using SPM12. Co-registration and spatial normalization of FP-CIT image conducted using T1-weighted magnetic resonance imaging (MRI). And then smoothing of normalized FP-CIT image was performed. Intensity normalization was performed using cerebellum as a reference region. With pre-defined volume of interest template, the specific binding ratio (SBR) of both side of caudate nucleus and putamen was calculated. Fluid attenuated inversion recovery MRI scans were used to evaluate WMH number and volume. SBRs of left and right caudate nucleus were correlated with age (r = -0.615; p < 0.0001; n = 48, r = -0.607; p < 0.0001; n = 48, respectively), high density lipoprotein cholesterol (r = 0.296; p = 0.041; n = 48, r = 0.29; p = 0.0455; n = 48, respectively), and WMH number (r = -0.459; p = 0.001; n = 48, r = -0.481; p = 0.0005; n = 48, respectively) and volume (r = -0.407; p = 0.0041; n = 48, r = -0.428; p = 0.0024; n = 48, respectively). DAT availability of patients who showed visually normal F-18 FP-CIT uptake was correlated with number and volume of WMH.

DTI Atlases Evaluations.

The cerebral atlas of diffusion tensor magnetic resonance image (DT-MRI, shorted as DTI) is one of the key issues in neuroimaging research. It is crucial for comparisons of neuronal structural integrity and connectivity across populations. Usually, the atlas is constructed by iteratively averaging the registered individual image. In tradition, the fuzzy group average image is easily generated in the initial stage, which is harmful to providing clear guidance for subsequent registration, to the performance of the final atlas. To solve this problem, an improved unbiased DTI atlas construction algorithm based on adaptive weights is proposed in this paper. The adaptive weighted strategy based on diffeomorphic deformable tensor registration is introduced. At the same time, the distance measure for tensors is used as a constraint condition, which ensures the unbiasedness of the atlas. Then, using 77 DTIs from the dataset in http://www.brain-development.org , three study-specific atlases, i.e. the constructed atlases of the proposed algorithm and two open-sourced algorithms (DTIAtlasBuilder and DTI-TK), are compared with two standardized atlases (IIT v. 4.1 and NTU-DSI-122-DTI). The performances of the atlases were evaluated in spatial normalization way with six region-based criteria (including Euclidean distances between diffusion tensors, Euclidean distances of the deviatoric tensors, standard deviation, overlaps of eigenvalue-eigenvector, cross-correlations and three sets angles of eigenvalue-eigenvector pairs between diffusion tensors) and three fiber-based criteria (including distances between fiber bundles, angles between fiber bundles and fiber property profile-based criteria). The experimental results showed that the overall performances of the study-specific atlases are better than those of the standardized atlases for specific datasets, and the comprehensive performance of the improved algorithm proposed in this paper is the best.

4DEMON: Integrating 40 Years of Data on PCB and Metal Contamination in Marine Sediments of the Belgian Part of the North Sea

The assessment of historical data is important to understand long-term changes in the marine environment. Whereas time series analyses based on monitoring data typically span one or two decades, this work aimed to integrate 40 years of monitoring and research data on polychlorinated biphenyls (PCBs) and metals in the Belgian Part of the North Sea (BPNS). Multiple challenges were encountered: sampling locations changed over time, different analytical methods were applied, different grain size fractions were analyzed, appropriate co-factors were not always analyzed, and measurement uncertainties were not always indicated. These issues hampered the use of readily available, highly standardized trend modeling approaches like those proposed by regional sea conventions such as OSPAR, named after the Oslo and Paris conventions.Therefore, we applied alternative approaches, allowing us to include most older historical data that have been obtained during the nineteen seventies and eighties. Our approach included reproducible and quality controlled procedures from data collection up to data assessment. It included spatial clustering, data normalization and parametric linear mixed effect modeling. A Ward hierarchical clustering was applied on recently obtained contaminant data, as the basis for a spatial division of the BPNS into five distinct areas with different contamination profiles. To minimize the risk of normalization errors for the metal data analyses, four normalization approaches were applied and mutually compared: granulometric and nickel (Ni) normalization, next to two hybrid normalization methods combining aluminum (Al) and iron (Fe) normalization. The long-term models revealed decreasing trends for most metals, except zinc (Zn) for which three out of four models showed increasing concentrations in all five zones of the BPNS. Offshore sediments contained the lowest normalized mercury (Hg) and cadmium (Cd) concentrations but high arsenic (As) concentrations. Trend analysis revealed a strong decrease in PCB concentrations in the nineteen eighties and nineties, followed by a slight increase over the last decade. The extended timeframe for contaminant assessment, as applied in this study, is of added value for scientists and policy makers, as the approach allows to detect trends and effects of anthropogenic activities within the marine environment within a broad perspective.

Global and Spatial Compartmental Interrelationships of Bone Density, Microstructure, Geometry and Biomechanics in the Distal Radius in a Colles' Fracture Study Using HR-pQCT.

BackgroundBone parameters derived from HR-pQCT have been investigated on a parameter-by-parameter basis for different clinical conditions. However, little is known regarding the interrelationships of bone parameters and the spatial distribution of these interrelationships. In this work: 1) we investigate compartmental interrelationships of bone parameters; 2) assess the spatial distribution of interrelationships of bone parameters; and 3) compare interrelationships of bone parameters between postmenopausal women with and without a recent Colles’ fracture.MethodsImages from the unaffected radius in fracture cases (n=84), and from the non-dominant radius of controls (n=98) were obtained using HR-pQCT. Trabecular voxel-based maps of local bone volume fraction (L.Tb.BV/TV), homogenized volumetric bone mineral density (H.Tb.BMD), homogenized μFEA-derived strain energy density (H.Tb.SED), and homogenized inter-trabecular distances (H.Tb.1/N) were generated; as well as surface-based maps of apparent cortical bone thickness (Surf.app.Ct.Th), porosity-weighted cortical bone thickness (Surf.Ct.SIT), mean cortical BMD (Surf.Ct.BMD), and mean cortical SED (Surf.Ct.SED). Anatomical correspondences across the parametric maps in the study were established via spatial normalization to a common template. Mean values of the parametric maps before spatial normalization were used to assess compartmental Spearman’s rank partial correlations of bone parameters (e.g., between H.Tb.BMD and L.Tb.BV/TV or between Surf.Ct.BMD and Surf.app.Ct.Th). Spearman’s rank partial correlations were also assessed for each voxel and vertex of the spatially normalized parametric maps, thus generating maps of Spearman’s rank partial correlation coefficients. Correlations were performed independently within each group, and compared between groups using the Fisher’s Z transformation.ResultsAll within-group global trabecular and cortical Spearman’s rank partial correlations were significant; and the correlations of H.Tb.BMD–L.Tb.BV/TV, H.Tb.BMD–H.Tb.1/N, L.Tb.BV/TV–H.Tb.1/N, Surf.Ct.BMD–Surf.Ct.SED and Surf.Ct.SIT–Surf.Ct.SED were significantly different between controls and fracture cases. The spatial analyses revealed significant heterogeneous voxel- and surface-based correlation coefficient maps across the distal radius for both groups; and the correlation maps of H.Tb.BMD–L.Tb.BV/TV, H.Tb.BMD–H.Tb.1/N, L.Tb.BV/TV–H.Tb.1/N, H.Tb.1/N–H.Tb.SED and Surf.app.Ct.Th - Surf.Ct.SIT yielded small clusters of significant correlation differences between groups.DiscussionThe heterogeneous spatial distribution of interrelationships of bone parameters assessing density, microstructure, geometry and biomechanics, along with their global and local differences between controls and fracture cases, may help us further understand different bone mechanisms of bone fracture.

Atlas construction and spatial normalisation to facilitate radiation-induced late effects research in childhood cancer

Reducing radiation-induced side effects is one of the most important challenges in paediatric cancer treatment. Recently, there has been growing interest in using spatial normalisation to enable voxel-based analysis of radiation-induced toxicities in a variety of patient groups. The need to consider three-dimensional distribution of doses, rather than dose-volume histograms, is desirable but not yet explored in paediatric populations. In this paper, we investigate the feasibility of atlas construction and spatial normalisation in paediatric radiotherapy. We used planning computed tomography (CT) scans from twenty paediatric patients historically treated with craniospinal irradiation to generate a template CT that is suitable for spatial normalisation. This childhood cancer population representative template was constructed using groupwise image registration. An independent set of 53 subjects from a variety of childhood malignancies was then used to assess the quality of the propagation of new subjects to this common reference space using deformable image registration (i.e. spatial normalisation). The method was evaluated in terms of overall image similarity metrics, contour similarity and preservation of dose-volume properties. After spatial normalisation, we report a dice similarity coefficient of 0.95 ± 0.05, 0.85 ± 0.04, 0.96 ± 0.01, 0.91 ± 0.03, 0.83 ± 0.06 and 0.65 ± 0.16 for brain and spinal canal, ocular globes, lungs, liver, kidneys and bladder. We then demonstrated the potential advantages of an atlas-based approach to study the risk of second malignant neoplasms after radiotherapy. Our findings indicate satisfactory mapping between a heterogeneous group of patients and the template CT. The poorest performance was for organs in the abdominal and pelvic region, likely due to respiratory and physiological motion and to the highly deformable nature of abdominal organs. More specialised algorithms should be explored in the future to improve mapping in these regions. This study is the first step toward voxel-based analysis in radiation-induced toxicities following paediatric radiotherapy.

Sex modifies APOE ε4 dose effect on brain tau deposition in cognitively impaired individuals.

Recent studies in cognitively unimpaired elderly individuals suggest that the APOE ε4 allele exerts a dosage-dependent effect on brain tau deposition. The aim of this study was to investigate sex differences in APOE ε4 gene dosage effects on brain tau deposition in cognitively impaired individuals using quantitative 18F-flortaucipir PET.Preprocessed 18F-flortaucipir tau PET images, T1-weighted structural MRI, demographic information, global cortical amyloid-β burden measured by 18F-florbetapir PET, CSF total tau and phosphorylated tau measurements were obtained from the Alzheimer’s Disease Neuroimaging Initiative database. Two hundred and sixty-eight cognitively impaired individuals with 146 APOE ε4 non-carriers and 122 carriers (85 heterozygotes and 37 homozygotes) were included in the study. An iterative reblurred Van Cittert iteration partial volume correction method was applied to all downloaded PET images. Magnetic resonance images were used for PET spatial normalization. Twelve regional standardized uptake value ratios relative to the cerebellum were computed in standard space. APOE ε4 dosage × sex interaction effect on 18F-flortaucipir standardized uptake value ratios was assessed using generalized linear models and sex-stratified analysis.We observed a significant APOE ε4 dosage × sex interaction effect on tau deposition in the lateral temporal, posterior cingulate, medial temporal, inferior temporal, entorhinal cortex, amygdala, parahippocampal gyrus regions after adjusting for age and education level (P < 0.05). The medial temporal, entorhinal cortex, amygdala and parahippocampal gyrus regions retained a significant APOE ε4 dosage × sex interaction effect on tau deposition after adjusting for global cortical amyloid-β (P < 0.05). In sex-stratified analysis, there was no significant difference in tau deposition between female homozygotes and heterozygotes (P > 0.05). In contrast, male homozygotes standardized uptake value ratios were significantly greater than heterozygotes or non-carriers throughout all 12 regions of interest (P < 0.05). Female heterozygotes exhibited significantly increased tau deposition compared to male heterozygotes in the orbitofrontal, posterior cingulate, lateral temporal, inferior temporal, entorhinal cortex, amygdala and parahippocampal gyrus (P < 0.05). Results from voxel-wise analysis were similar to the ones obtained from regions of interest analysis.Our findings indicate that an APOE ε4 dosage effect on brain region-specific tau deposition exists in males, but not females. These results have important clinical implications towards developing sex and genotype-guided therapeutics in Alzheimer’s disease and uncovers a potential explanation underlying differential APOE ε4-associated Alzheimer’s risk in males and females.

Simultaneously acquired PET and ASL imaging biomarkers may be helpful in differentiating progression from pseudo-progression in treated gliomas.

The aim of this work was investigating the methods based on coupling cerebral perfusion (ASL) and amino acid metabolism ([18F]DOPA-PET) measurements to evaluate the diagnostic performance of PET/MRI in glioma follow-up. Images were acquired using a 3-T PET/MR system, on a prospective cohort of patients addressed for possible glioma progression. Data were preprocessed with statistical parametric mapping (SPM), including registration on T1-weighted images, spatial and intensity normalization, and tumor segmentation. As index tests, tumor isocontour maps of [18F]DOPA-PET and ASL T-maps were created and metabolic/perfusion abnormalities were evaluated with the asymmetry index z-score. SPM map analysis of significant size clusters and semi-quantitative PET and ASL map evaluation were performed and compared to the gold standard diagnosis. Lastly, ASL and PET topography of significant clusters was compared to that of the initial tumor. Fifty-eight patients with unilateral treated glioma were included (34 progressions and 24 pseudo-progressions). The tumor isocontour maps and T-maps showed the highest specificity (100%) and sensitivity (94.1%) for ASL and [18F]DOPA analysis, respectively. The sensitivity of qualitative SPM maps and semi-quantitative rCBF and rSUV analyses were the highest for glioblastoma. Tumor isocontour T-maps and combined analysis of CBF and [18F]DOPA-PET uptake allow achieving high diagnostic performance in differentiating between progression and pseudo-progression in treated gliomas. The sensitivity is particularly high for glioblastomas. • Applied separately, MRI and PET imaging modalities may be insufficient to characterize the brain glioma post-therapeutic profile. • Combined ASL and [18F]DOPA-PET map analysis allows differentiating between tumor progression and pseudo-progression.

Development of brain atlases for early-to-middle adolescent collision-sport athletes

Human brains develop across the life span and largely vary in morphology. Adolescent collision-sport athletes undergo repetitive head impacts over years of practices and competitions, and therefore may exhibit a neuroanatomical trajectory different from healthy adolescents in general. However, an unbiased brain atlas targeting these individuals does not exist. Although standardized brain atlases facilitate spatial normalization and voxel-wise analysis at the group level, when the underlying neuroanatomy does not represent the study population, greater biases and errors can be introduced during spatial normalization, confounding subsequent voxel-wise analysis and statistical findings. In this work, targeting early-to-middle adolescent (EMA, ages 13–19) collision-sport athletes, we developed population-specific brain atlases that include templates (T1-weighted and diffusion tensor magnetic resonance imaging) and semantic labels (cortical and white matter parcellations). Compared to standardized adult or age-appropriate templates, our templates better characterized the neuroanatomy of the EMA collision-sport athletes, reduced biases introduced during spatial normalization, and exhibited higher sensitivity in diffusion tensor imaging analysis. In summary, these results suggest the population-specific brain atlases are more appropriate towards reproducible and meaningful statistical results, which better clarify mechanisms of traumatic brain injury and monitor brain health for EMA collision-sport athletes.

Preferential tumor localization in relation to 18F-FDOPA uptake for lower-grade gliomas.

Although tumor localization and 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas. Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping. Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.

Statistical parametric mapping of three-dimensional local activity distribution of skeletal muscle using magnetic resonance imaging (MRI)

Analysis of the internal local activity distribution in human skeletal muscles is important for managing muscle fatigue/pain and dysfunction. However, no method is established for three-dimensional (3D) statistical analysis of features of activity regions common to multiple subjects during voluntary motor tasks. We investigated the characteristics of muscle activity distribution from the data of ten healthy subjects (29 ± 1 year old, 2 women) during voluntary teeth clenching under two different occlusal conditions by applying spatial normalization and statistical parametric mapping (SPM) to analysis of muscle functional magnetic resonance imaging (mfMRI) using increase in transverse relaxation time (T2) of the skeletal muscle induced by exercise. The expansion of areas with significant T2 increase was observed in the masticatory muscles after clenching with molar loss comparing with intact dentition. The muscle activity distribution characteristics common to a group of subjects, i.e., the active region in the temporal muscle ipsilateral to the side with the molar loss and medial pterygoid muscle contralateral to the side with the molar loss, were clarified in 3D by applying spatial normalization and SPM to mfMRI analysis. This method might elucidate the functional distribution within the muscles and the localized muscular activity related to skeletal muscle disorders.

Brain Glucose Metabolism in Cerebral Amyloid Angiopathy: An FDG-PET Study.

The in vivo diagnosis of cerebral amyloid angiopathy (CAA) is currently based on the Boston criteria, which largely rely on hemorrhagic features on brain magnetic resonance imaging. Adding to these criteria 18F-fluoro-deoxy-D-glucose (FDG) positron emission tomography, a widely available imaging modality, might improve their accuracy. Here we tested the hypothesis that FDG uptake is reduced in posterior cortical areas, particularly the primary occipital cortex, which pathologically bear the brunt of vascular Aβ deposition. From a large memory clinic database, we retrospectively included all patients in whom both brain magnetic resonance imaging and FDG positron emission tomography had been obtained as part of routine clinical care and who fulfilled the Boston criteria for probable CAA. None had a history of symptomatic intracerebral hemorrhage. FDG data processing involved (1) spatial normalization to the Montreal Neurology Institute/International Consortium for Brain Mapping 152 space and (2) generation of standardized FDG uptake (relative standardized uptake value; relative to the pons). The relative standardized uptake value data obtained in 13 regions of interest sampling key cortical areas and the cerebellum were compared between the CAA and age-matched control groups using 2 separate healthy subject databases and image-processing pipelines. The presence of significant hypometabolism (2-tailed P<0.05) was assessed for the bilaterally averaged regions-of-interest relative standardized uptake values. Fourteen patients fulfilling the Boston criteria for probable CAA (≥2 exclusively lobar microbleeds) were identified. Significant hypometabolism (P range, 0.047 to <0.0001) consistently affected the posterior cortical areas, including the superior and inferior parietal, primary visual, lateral occipital, lateral temporal, precuneus, and posterior cingulate regions of interest. The anterior cortical areas were marginally or not significantly hypometabolic, and the cerebellum was spared. Supporting our hypothesis, significant glucose hypometabolism predominantly affected posterior cortical regions, including the visual cortex. These findings from a small sample may have diagnostic implications but require replication in larger prospective studies. In addition, whether they generalize to CAA-related symptomatic intracerebral hemorrhage warrants specific studies.

Validation of Group-wise Registration for Surface-based Functional MRI Analysis.

Resting-state functional MRI (rsfMRI) provides important information for studying and mapping the activities and functions of the brain. Conventionally, rsfMRIs are often registered to structural images in the Euclidean space without considering cortical surface geometry. Meanwhile, a surface-based representation offers a relaxed coordinate chart, but this still requires surface registration for group-wise data analysis. In this work, we investigate the performance of two existing surface registration methods in a surface-based rsfMRI analysis framework: FreeSurfer and Hierarchical Spherical Deformation (HSD). To minimize registration bias, we establish shape correspondence using both methods in a group-wise manner that estimates the unbiased average of a given cohort. To evaluate their performance, we focus on neuroanatomical alignment as well as the amount of distortion that can potentially bias surface tessellation for secondary level rsfMRI data analyses. In the pilot analysis, we examine a single timepoint of imaging data from 100 subjects out of an aging cohort. Overall, HSD establishes improved shape correspondence with reduced mean curvature deviation (10.94% less on average per subject, paired t-test: p <10-10) and reduced registration distortion (FreeSurfer: average 41.91% distortion per subject, HSD: 18.63%, paired t-test: p <10-10). Furthermore, HSD introduces less distortion than FreeSurfer in the areas identified in the individual components that were extracted by surface-based independent component analysis (ICA) after spatial smoothing and time series normalization. Consequently, we show that FreeSurfer capture individual components with globally similar but locally different patterns in ICA in visual inspection.

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation.

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality medical data with a notable domain shift. Given that specific annotated imaging modalities may not be accessible nor complete. Our proposed solution is based on the cross-modality synthesis of medical images to reduce the costly annotation burden by radiologists and bridge the domain gap in radiological images. We present a novel approach for image-to-image translation in medical images, capable of supervised or unsupervised (unpaired image data) setups. Built upon adversarial training, we propose a learnable self-attentive spatial normalization of the deep convolutional generator network's intermediate activations. Unlike previous attention-based image-to-image translation approaches, which are either domain-specific or require distortion of the source domain's structures, we unearth the importance of the auxiliary semantic information to handle the geometric changes and preserve anatomical structures during image translation. We achieve superior results for cross-modality segmentation between unpaired MRI and CT data for multi-modality whole heart and multi-modal brain tumor MRI (T1/T2) datasets compared to the state-of-the-art methods. We also observe encouraging results in cross-modality conversion for paired MRI and CT images on a brain dataset. Furthermore, a detailed analysis of the cross-modality image translation, thorough ablation studies confirm our proposed method's efficacy.

Effect of brain normalization methods on the construction of functional connectomes from resting‐state functional MRI in patients with gliomas

Spatial normalization is an essential step in resting-state functional MRI connectomic analysis with atlas-based parcellation, but brain lesions can confound it. Cost-function masking (CFM) is a popular compensation approach, but may not benefit modern normalization methods. This study compared three normalization methods with and without CFM and determined their impact on connectomic measures in patients with glioma. Fifty patients with glioma were included. T1 -weighted images were normalized using three different methods in SPM12, with and without CFM, which were then overlaid on the ICBM152 template and scored by two neuroradiologists. The Dice coefficient of gray-matter correspondence was also calculated. Normalized resting-state functional MRI data were parcellated using the AAL90 atlas to construct an individual connectivity matrix and calculate connectomic measures. The R2 among the different normalization methods was calculated for the connectivity matrices and connectomic measures. The older method (Original) performed significantly worse than the modern methods (Default and DARTEL; P < .005 in observer ranking). The use of CFM did not significantly improve the normalization results. The Original method had lower correlation with the Default and DARTEL methods (R2 = 0.71-0.74) than Default with DARTEL (R2 = 0.96) in the connectivity matrix. The clustering coefficient appears to be the most, and modularity the least, sensitive connectomic measures to normalization performance. The spatial normalization method can have an impact on resting-state functional MRI connectome and connectomic measures derived using atlas-based brain parcellation. In patients with glioma, this study demonstrated that Default and DARTEL performed better than the Original method, and that CFM made no significant difference.

Development and evaluation of a high performance T1-weighted brain template for use in studies on older adults.

Τhe accuracy of template‐based neuroimaging investigations depends on the template's image quality and representativeness of the individuals under study. Yet a thorough, quantitative investigation of how available standardized and study‐specific T1‐weighted templates perform in studies on older adults has not been conducted. The purpose of this work was to construct a high‐quality standardized T1‐weighted template specifically designed for the older adult brain, and systematically compare the new template to several other standardized and study‐specific templates in terms of image quality, performance in spatial normalization of older adult data and detection of small inter‐group morphometric differences, and representativeness of the older adult brain. The new template was constructed with state‐of‐the‐art spatial normalization of high‐quality data from 222 older adults. It was shown that the new template (a) exhibited high image sharpness, (b) provided higher inter‐subject spatial normalization accuracy and (c) allowed detection of smaller inter‐group morphometric differences compared to other standardized templates, (d) had similar performance to that of study‐specific templates constructed with the same methodology, and (e) was highly representative of the older adult brain.

Розробка математичної моделі перемикання електричної поляризації у сегнетоелектричному конденсаторі

In this paper, a mathematical model of switching the electrical polarization of a ferroelectric capacitor was developed, which adequately reflects the processes of writing and reading in the elements of FRAM-memory and is suitable for developing automated design of ferroelectric storage elements and devices. Physical models of switching electrical polarization in a ferroelectric capacitor are found only in isolated cases of crystallization under certain assumptions about the dimension of domains, the processes of their nucleation, growth and overlap. Therefore, the work carried out the transfer of the known geometric-probabilistic model of melt crystallization to the processes of repolarization of ferroelectrics. For this crystallization model, two variants of its practical implementation have been developed — for χ- and β-processes. Accordingly, in the mathematical model we can distinguish two components, calling them χ- and β-models of switching polarization in a ferroelectric capacitor. The difference between the developed model and others is that in the crystallization model the initial value of polarization is introduced and mixed (temporal and spatial) normalization of the parameters of the ferroelectric material is performed. In particular, the concept of characteristic time is introduced, which is the time of doubling the radius of embryos in fields with intensities much larger than the activation fields; characteristic volume, which for the χ-process is equal to the volume repolarized by germination over the characteristic time, and for the β-process — the initial volume, polarized in the direction of the field before its application and the relative field of activation of germination and growth of domains. Generalized normalized models with mixed rationing proved to be more convenient for setting certain requirements for the parameters of ferroelectric material in order to obtain the specified characteristics of ferroelectric storage elements in terms of speed and intensity of switching currents.

Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network.

Brain atlases are of fundamental importance for analyzing the dynamic neurodevelopment in fetal brain studies. Since the brain size, shape, and anatomical structures change rapidly during the prenatal period, it is essential to construct a spatiotemporal (4D) atlas equipped with tissue probability maps, which can preserve sharper early brain folding patterns for accurately characterizing dynamic changes in fetal brains and provide tissue prior informations for related tasks, e.g., segmentation, registration, and parcellation. In this work, we propose a novel unsupervised age-conditional learning framework to build temporally continuous fetal brain atlases by incorporating tissue segmentation maps, which outperforms previous traditional atlas construction methods in three aspects. First, our framework enables learning age-conditional deformable templates by leveraging the entire collection. Second, we leverage reliable brain tissue segmentation maps in addition to the low-contrast noisy intensity images to enhance the alignment of individual images. Third, a novel loss function is designed to enforce the similarity between the learned tissue probability map on the atlas and each subject tissue segmentation map after registration, thereby providing extra anatomical consistency supervision for atlas building. Our 4D temporally-continuous fetal brain atlases are constructed based on 82 healthy fetuses from 22 to 32 gestational weeks. Compared with the atlases built by the state-of-the-art algorithms, our atlases preserve more structural details and sharper folding patterns. Together with the learned tissue probability maps, our 4D fetal atlases provide a valuable reference for spatial normalization and analysis of fetal brain development.