Average Template Research Articles

Using three-dimensional average facial meshes to determine nasolabial soft tissue deformity in adult UCLP patients

Background and purposeThere is limited literature discussing the residual nasolabial deformity of adult patients prior to undergoing orthognathic surgery. The purpose of this study is to determine the site and severity of the residual nasolabial soft tissue deformity between adult unilateral cleft lip and palate (UCLP) patients and a non-cleft reference group, prior to orthognathic surgery. Material and methodsSixteen adult male UCLP patients, who all received primary lip and palate surgery according to a standardised Hong Kong protocol were recruited for this study. Facial images of each individual were captured using three-dimensional (3D) stereophotogrammetry and compared to a previous published Hong Kong non-cleft reference group of 48 male adults. Using two-sample t-tests differences in linear and angular measurements and asymmetry scores were evaluated between the two groups. In addition a “conformed” average UCLP facial template was superimposed and compared to conformed average non-cleft reference group facial template. Reproducibility of the measurements were assessed using Students paired t-tests and coefficients of reliability. Main findingsSignificant differences in linear and angular measurements and asymmetry scores were observed between the two groups (p < 0.05). Adult UCLP patients showed significantly narrower nostril floor widths, longer columella length on the unaffected side, a wider nose, shorter cutaneous lip height, shorter upper lip length and shorter philtrum length. Prior to orthognathic surgery adult UCLP patients showed significantly more facial asymmetry. Superimposition of the average facial meshes clearly showed the site and severity of the deficiency in the x, y and z-directions. ConclusionsMany of the nasolabial characteristics reported to be present in children following primary UCLP repair continue into adulthood. The detrimental soft tissue effects of orthognathic surgery for UCLP patients may be different to non-cleft individuals; and as such the site and severity of the residual deformity should be assessed prior to surgery.

Averaging of motion capture recordings for movements\u2019 templates generation

In this paper we propose, describe and evaluate the novel motion capture (MoCap) data averaging framework. It incorporates hierarchical kinematic model, angle coordinates’ preprocessing methods, that recalculate the original MoCap recording making it applicable for further averaging algorithms, and finally signals averaging processing. We have tested two signal averaging methods namely Kalman Filter (KF) and Dynamic Time Warping barycenter averaging (DBA). The propose methods have been tested on MoCap recordings of elite Karate athlete, multiple champion of Oyama karate knockdown kumite who performed 28 different karate techniques repeated 10 times each. The proposed methods proved to have not only high effectiveness measured with root-mean-square deviation (4.04 ± 5.03 degrees for KF and 5.57 ± 6.27 for DBA) and normalized Dynamic Time Warping distance (0.90 ± 1.58 degrees for KF and 0.93 ± 1.23 for DBA), but also the reconstruction and visualization of those recordings persists all crucial aspects of those complicated actions. The proposed methodology has many important applications in classification, clustering, kinematic analysis and coaching. Our approach generates an averaged full body motion template that can be practically used for example for human actions recognition. In order to prove it we have evaluated templates generated by our method in human action classification tasks using DTW classifier. We have made two experiments. In first leave - one - out cross - validation we have obtained 100% correct recognitions. In second experiment when we classified recordings of one person using templates of another recognition rate 94.2% was obtained.

T35. DIFFUSION MEASURES OF EXTRACELLULAR FREE WATER IN A NON-HUMAN PRIMATE MODEL OF MATERNAL IMMUNE ACTIVATION: EXPLORING NEUROIMMUNE MECHANISMS OF PSYCHIATRIC DISORDERS

BackgroundEvidence has been accumulating for an immune-based component of psychiatric disorder etiology, particularly schizophrenia. Early epidemiological studies found an increased incidence of schizophrenia in offspring of mothers who had an infection during pregnancy. Recent work has identified genetic links to the MHC complex, pro-inflammatory cytokine elevations in cerebrospinal fluid and plasma. We have developed a non-human primate (NHP) model of maternal immune activation (MIA) using a modified form of the viral mimic polyIC (polyICLC) examine the relationship between altered neuorimmune function may contribute to psychosis risk through effects on the developing brain and behavior of NHP offspring. In a previous cohort of MIA-exposed offspring, our group observed evidence for increased pre-synaptic dopamine levels in the striatum using 6-[18F]fluoro-L-m-tyrosine (FMT) positron emission tomography, in addition to pubertal-onset behavioral abnormalities, which may model part of the neurodevelopmental pathway towards psychosis. This study builds on this model and examines the effect of maternal immune activation on in vivo--extracellular free water--a diffusion magnetic resonance imaging measure obtained with a multi-shell acquisition. We sought to test the hypothesis that offspring of pregnant monkeys who received polyICLC injections at the end of the first trimester would show increased extracellular free water compared to control offspring.MethodsFourteen pregnant rhesus monkeys (Macaca mulatta) receiving polyICLC at the end of the first trimester were compared to 14 controls. The offspring from both groups underwent a multi-shell diffusion MRI scan at 3 Tesla. Diffusion data was collected when the offspring were one month, 6 months, and 12 months of age. Six month preliminary findings are currently presented. Diffusion images were aligned to individual subject MPRAGE scans. Individual subject structural scans were then nonlinearly aligned to generate a common group average template and the group average template was subsequently nonlinearly aligned to a neurodevelopmental rhesus atlas. For this preliminary analysis, the frontal cortex was selected as an a priori region of interest in addition to the more global whole-brain gray and white matter masks.ResultsSix month old MIA-exposed rhesus offspring showed a trend for increased whole-brain white matter extracellular free water (p=.09) with no significant difference in whole-brain gray matter free water (p=.27) compared to control offspring. However, analysis of the frontal ROI revealed significantly increased gray matter free water in the left hemisphere (p=.013) with a trend towards increased gray matter free water in the right hemisphere (p=.081). There were no significant differences between MIA-exposed and control offspring in basic motor and reflex development or growth trajectories.DiscussionThese data suggest that despite the lack of behavioral abnormalities at this early age, extracellular free water values are increased in MIA-exposed offspring, particularly in frontal gray matter. More global whole-brain free water group differences did not reach statistical significance, which may indicate some regional specificity to these changes early in development. The NHP MIA model complements the human schizophrenia literature in which extracellular free water increases have been repeatedly identified. Ultimately, these data provide validation of the clinical relevance of the NHP MIA model and improve our understanding of neuroimmune mechanisms in the development of psychiatric disorders, particularly schizophrenia.

A comparison of publicly available linear MRI stereotaxic registration techniques

IntroductionLinear registration to a standard space is one of the major steps in processing and analyzing magnetic resonance images (MRIs) of the brain. Here we present an overview of linear stereotaxic MRI registration and compare the performance of 5 publicly available and extensively used linear registration techniques in medical image analysis. MethodsA set of 9693 T1-weighted MR images were obtained for testing from 4 datasets: ADNI, PREVENT-AD, PPMI, and HCP, two of which have multi-center and multi-scanner data and three of which have longitudinal data. Each individual native image was linearly registered to the MNI ICBM152 average template using five versions of MRITOTAL from MINC tools, FLIRT from FSL, two versions of Elastix, spm_affreg from SPM, and ANTs linear registration techniques. Quality control (QC) images were generated from the registered volumes and viewed by an expert rater to assess the quality of the registrations. The QC image contained 60 sub-images (20 of each of axial, sagittal, and coronal views at different levels throughout the brain) overlaid with contours of the ICBM152 template, enabling the expert rater to label the registration as acceptable or unacceptable. The performance of the registration techniques was then compared across different datasets. In addition, the effect of image noise, intensity non-uniformity, age, head size, and atrophy on the performance of the techniques was investigated by comparing differences between age, scaling factor, ventricle volume, brain volume, and white matter hyperintensity (WMH) volumes between passed and failed cases for each method. ResultsThe average registration failure rate among all datasets was 27.41%, 27.14%, 12.74%, 13.03%, 0.44% for the five versions of MRITOTAL techniques, 8.87% for ANTs, 11.11% for FSL, 12.35% for Elastix Affine, 24.40% for Elastix Similarity, and 30.66% for SPM. There were significant effects of signal to noise ratio, image intensity non-uniformity estimates, as well as age, head size, and atrophy related changes between passed and failed registrations. ConclusionOur experiments show that the Revised BestLinReg had the best performance among the evaluated registration techniques while all techniques performed worse for images with higher levels of noise and non-uniformity as well as atrophy related changes.

Constructing Statistically Unbiased Cortical Surface Templates Using Feature-Space Covariance.

The choice of surface template plays an important role in cross-sectional subject analyses involving cortical brain surfaces because there is a tendency toward registration bias given variations in inter-individual and inter-group sulcal and gyral patterns. In order to account for the bias and spatial smoothing, we propose a feature-based unbiased average template surface. In contrast to prior approaches, we factor in the sample population covariance and assign weights based on feature information to minimize the influence of covariance in the sampled population. The mean surface is computed by applying the weights obtained from an inverse covariance matrix, which guarantees that multiple representations from similar groups (e.g., involving imaging, demographic, diagnosis information) are down-weighted to yield an unbiased mean in feature space. Results are validated by applying this approach in two different applications. For evaluation, the proposed unbiased weighted surface mean is compared with un-weighted means both qualitatively and quantitatively (mean squared error and absolute relative distance of both the means with baseline). In first application, we validated the stability of the proposed optimal mean on a scan-rescan reproducibility dataset by incrementally adding duplicate subjects. In the second application, we used clinical research data to evaluate the difference between the weighted and unweighted mean when different number of subjects were included in control versus schizophrenia groups. In both cases, the proposed method achieved greater stability that indicated reduced impacts of sampling bias. The weighted mean is built based on covariance information in feature space as opposed to spatial location, thus making this a generic approach to be applicable to any feature of interest.

7T MRI subthalamic nucleus atlas for use with 3T MRI

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces motor symptoms in most patients with Parkinson disease (PD), yet may produce untoward effects. Investigation of DBS effects requires accurate localization of the STN, which can be difficult to identify on magnetic resonance images collected with clinically available 3T scanners. The goal of this study is to develop a high-quality STN atlas that can be applied to standard 3T images. We created a high-definition STN atlas derived from seven older participants imaged at 7T. This atlas was nonlinearly registered to a standard template representing 56 patients with PD imaged at 3T. This process required development of methodology for nonlinear multimodal image registration. We demonstrate mm-scale STN localization accuracy by comparison of our 3T atlas with a publicly available 7T atlas. We also demonstrate less agreement with an earlier histological atlas. STN localization error in the 56 patients imaged at 3T was less than 1mm on average. Our methodology enables accurate STN localization in individuals imaged at 3T. The STN atlas and underlying 3T average template in MNI space are freely available to the research community. The image registration methodology developed in the course of this work may be generally applicable to other datasets.

Fabric Defect Detection Based on Pattern Template Correction

This paper proposes a novel template-based correction (TC) method for the defect detection on images with periodic structures. In this method, a fabric image is segmented into lattices according to variation regularity, and correction is applied to reduce the effect of misalignment among lattices. Also, defect-free lattices are chosen for establishing an average template as a uniform reference. Furthermore, the defect detection procedure is composed of two steps, namely, defective lattices locating and defect shape outlining. Defective lattices locating is based on classification for defect-free and defective patterns, which involves an improved E-V method with template-based correction and centralized processing, while defect shape outlining provides pixel-level results by threshold segmentation. In this paper we also present some experiments on fabric defect detection. Experimental results show that the proposed method is effective.

Meeting the Cool Neighbors. XII. An Optically Anchored Analysis of the Near-infrared Spectra of L Dwarfs

Abstract Discrepancies between competing optical and near-infrared (NIR) spectral typing systems for L dwarfs have motivated us to search for a classification scheme that ties the optical and NIR schemes together, and addresses complexities in the spectral morphology. We use new and extant optical and NIR spectra to compile a sample of 171 L dwarfs, including 27 low-gravity β and γ objects, with spectral coverage from 0.6–2.4 μm. We present 155 new low-resolution NIR spectra and 19 new optical spectra. We utilize a method for analyzing NIR spectra that partially removes the broad-band spectral slope and reveals similarities in the absorption features between objects of the same optical spectral type. Using the optical spectra as an anchor, we generate near-infrared spectral average templates for L0–L8, L0–L4γ, and L0–L1β type dwarfs. These templates reveal that NIR spectral morphologies are correlated with the optical types. They also show the range of spectral morphologies spanned by each spectral type. We compare low-gravity and field-gravity templates to provide recommendations on the minimum required observations for credibly classifying low-gravity spectra using low-resolution NIR data. We use the templates to evaluate the existing NIR spectral standards and propose new ones where appropriate. Finally, we build on the work of Kirkpatrick et al. to provide a spectral typing method that is tied to the optical and can be used when only H or K band data are available. The methods we present here provide resolutions to several long-standing issues with classifying L dwarf spectra and could also be the foundation for a spectral classification scheme for cloudy exoplanets.

Automatic delineation of brain regions on MRI and PET images from the pig

BackgroundThe increasing use of the pig as a research model in neuroimaging requires standardized processing tools. For example, extraction of regional dynamic time series from brain PET images requires parcellation procedures that benefit from being automated. Comparison with existing methodsManual inter-modality spatial normalization to a MRI atlas is operator-dependent, time-consuming, and can be inaccurate with lack of cortical radiotracer binding or skull uptake. New methodA parcellated PET template that allows for automatic spatial normalization to PET images of any radiotracer. ResultsMRI and [11C]Cimbi-36 PET scans obtained in sixteen pigs made the basis for the atlas. The high resolution MRI scans allowed for creation of an accurately averaged MRI template. By aligning the within-subject PET scans to their MRI counterparts, an averaged PET template was created in the same space. We developed an automatic procedure for spatial normalization of the averaged PET template to new PET images and hereby facilitated transfer of the atlas regional parcellation. Evaluation of the automatic spatial normalization procedure found the median voxel displacement to be 0.22±0.08mm using the MRI template with individual MRI images and 0.92±0.26mm using the PET template with individual [11C]Cimbi-36 PET images. We tested the automatic procedure by assessing eleven PET radiotracers with different kinetics and spatial distributions by using perfusion-weighted images of early PET time frames. ConclusionWe here present an automatic procedure for accurate and reproducible spatial normalization and parcellation of pig PET images of any radiotracer with reasonable blood-brain barrier penetration.

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units () in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

Whole mouse brain imaging using optical coherence tomography: reconstruction, normalization, segmentation, and comparison with diffusion MRI.

An automated massive histology setup combined with an optical coherence tomography (OCT) microscope was used to image a total of [Formula: see text] whole mouse brains. Each acquisition generated a dataset of thousands of OCT volumetric tiles at a sampling resolution of [Formula: see text]. This paper describes techniques for reconstruction and segmentation of the sliced brains. In addition to the measured OCT optical reflectivity, a single scattering photon model was used to compute the attenuation coefficients within each tissue slice. Average mouse brain templates were generated for both the OCT reflectivity and attenuation contrasts and were used with an [Formula: see text]-tissue segmentation algorithm. To better understand the brain tissue OCT contrast origin, one of the mouse brains was acquired using dMRI and coregistered to its corresponding assembled brain. Our results indicate that the optical reflectivity in a fiber bundle varies with its orientation, its fiber density, and the number of fiber orientations it contains. The OCT mouse brain template generation and coregistration to dMRI data demonstrate the potential of this massive histology technique to pursue cross-sectional, multimodal, and multisubject investigations of small animal brains.

SQSTM1 MUTATIONS IN FRONTOTEMPORAL DEMENTIA ARE ASSOCIATED WITH ASYMMETRICAL FOCAL TEMPORAL LOBE ATROPHY

FTD is a common cause of young onset dementia and in around a third of cases is genetic. Recently mutations in SQSTM1 have been shown to be a rare cause of familial FTD. Little is known about the clinical or neuroanatomical phenotype at present. In this study, we investigated the pattern of grey matter atrophy in a group of patients with SQSTM1-associated FTD. SQSTM1 variants known to be a cause of familial FTD, or strongly increase risk, were found in four patients in the UCL FTD DNA cohort (n=440): two P392L, 1 E155K and 1 E396 frameshift mutation. The patient with the E396fs mutation was also found to have a C9orf72 expansion. The clinical diagnoses in the four patients were behavioural variant FTD, FTD with motor neurone disease, corticobasal syndrome and primary progressive aphasia. The mean (standard deviation) age at onset was 59.0 (5.9). All patients had undergone a T1-weighted magnetic resonance imaging scan acquired on a 3T Siemens Trio scanner: age at scan 65.8 (6.4). Their imaging was compared with 24 age- and gender-matched healthy controls (age: 66.5 (5.2)). We undertook a voxel-based morphometry (VBM) analysis comparing the SQSTM1 mutation carriers and the controls, correcting for age, gender and total intracranial volume. Statistical parametric maps were thresholded at p<0.05 after family-wise error correction and rendered on a study-specific average group T1-weighted MRI template image in MNI space. Grey matter atrophy was asymmetrical with three patients having right-sided dominant atrophy and one left-sided. For the analysis we flipped the scan in the midsagittal plane of the patient with left-sided atrophy so that the hemisphere in which there was predominant atrophy was the same in all four cases. The VBM analysis showed evidence of focal involvement of the antero-inferior-medial temporal lobe, particularly affecting the temporal pole, amygdala, hippocampus, entorhinal cortex, parahippocampal gyrus, and fusiform gyrus. There was an anterior-posterior gradient of atrophy as well as inferior-superior and medial-lateral gradients. In summary, patients with SQSTM1 mutations can have a varied clinical phenotype but appear to be particularly associated with focal temporal lobe atrophy that can predominantly affect the right or left hemisphere.

An Approach for Generating an Average Bone Template With Semantic Parameters

To facilitate the design of the serialized implants and to satisfy the requirements of the population, a novel method is put forward for constructing an average bone model (ABM) with semantic parameters as a template. First, the ABM is created from the existing bone models, among which each bone has an equal contribution to the ABM. Second, combined with medical semantics, some characteristic points and semantic parameters are defined on the ABM, and then, parameter values for each bone can be automatically obtained through its registration and deformation to the ABM. Finally, an average bone template (ABT) is constructed by configuring the semantic parameters and by building the constraints between parameters. Taking 100 femur models as samples, we construct the ABT, and the template can be easily extended to generate a new average template through the given average equation.

Quantification of rectifications for the Northwestern University Flexible Sub-Ischial Vacuum Socket.

The fit and function of a prosthetic socket depend on the prosthetist's ability to design the socket's shape to distribute load comfortably over the residual limb. We recently developed a sub-ischial socket for persons with transfemoral amputation: the Northwestern University Flexible Sub-Ischial Vacuum Socket. This study aimed to quantify the rectifications required to fit the Northwestern University Flexible Sub-Ischial Vacuum Socket to teach the technique to prosthetists as well as provide a computer-aided design-computer-aided manufacturing option. Development project. A program was used to align scans of unrectified and rectified negative molds and calculate shape change as a result of rectification. Averaged rectifications were used to create a socket template, which was shared with a central fabrication facility engaged in provision of Northwestern University Flexible Sub-Ischial Vacuum Sockets to early clinical adopters. Feedback regarding quality of fitting was obtained. Rectification maps created from 30 cast pairs of successfully fit Northwestern University Flexible Sub-Ischial Vacuum Sockets confirmed that material was primarily removed from the positive mold in the proximal-lateral and posterior regions. The template was used to fabricate check sockets for 15 persons with transfemoral amputation. Feedback suggested that the template provided a reasonable initial fit with only minor adjustments. Rectification maps and template were used to facilitate teaching and central fabrication of the Northwestern University Flexible Sub-Ischial Vacuum Socket. Minor issues with quality of initial fit achieved with the template may be due to inability to adjust the template to patient characteristics (e.g. tissue type, limb shape) and/or the degree to which it represented a fully mature version of the technique. Clinical relevance Rectification maps help communicate an important step in the fabrication of the Northwestern University Flexible Sub-Ischial Vacuum Socket facilitating dissemination of the technique, while the average template provides an alternative fabrication option via computer-aided design-computer-aided manufacturing and central fabrication.

Real‐time ballistocardiographic artifact reduction using the k‐teager energy operator detector and multi‐channel referenced adaptive noise cancelling

ABSTRACTThe simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recording technique has recently received considerable attention and has been used in many studies on cognition and neurological disease. EEG‐fMRI simultaneous recording has the advantage of enabling the monitoring of brain activity with both high temporal resolution and high spatial resolution in real time. The successful removal of the ballistocardiographic (BCG) artifact from the EEG signal recorded during an MRI is an important prerequisite for real‐time EEG‐fMRI joint analysis. We have developed a new framework dedicated to BCG artifact removal in real‐time. This framework includes a new real‐time R‐peak detection method combining a k‐Teager energy operator, a thresholding detector, and a correlation detector, as well as a real‐time BCG artifact reduction procedure combining average artifact template subtraction and a new multi‐channel referenced adaptive noise cancelling method. Our results demonstrate that this new framework is efficient in the real‐time removal of the BCG artifact. The multi‐channel adaptive noise cancellation (mANC) method performs better than the traditional ANC method in eliminating the BCG residual artifact. In addition, the computational speed of the mANC method fulfills the requirements of real‐time EEG‐fMRI analysis. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 209–215, 2016

Computation of a high-resolution MRI 3D stereotaxic atlas of the sheep brain.

The sheep model was first used in the fields of animal reproduction and veterinary sciences and then was utilized in fundamental and preclinical studies. For more than a decade, magnetic resonance (MR) studies performed on this model have been increasingly reported, especially in the field of neuroscience. To contribute to MR translational neuroscience research, a brain template and an atlas are necessary. We have recently generated the first complete T1-weighted (T1W) and T2W MR population average images (or templates) of in vivo sheep brains. In this study, we 1) defined a 3D stereotaxic coordinate system for previously established in vivo population average templates; 2) used deformation fields obtained during optimized nonlinear registrations to compute nonlinear tissues or prior probability maps (nlTPMs) of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) tissues; 3) delineated 25 external and 28 internal sheep brain structures by segmenting both templates and nlTPMs; and 4) annotated and labeled these structures using an existing histological atlas. We built a quality high-resolution 3D atlas of average in vivo sheep brains linked to a reference stereotaxic space. The atlas and nlTPMs, associated with previously computed T1W and T2W in vivo sheep brain templates and nlTPMs, provide a complete set of imaging space that are able to be imported into other imaging software programs and could be used as standardized tools for neuroimaging studies or other neuroscience methods, such as image registration, image segmentation, identification of brain structures, implementation of recording devices, or neuronavigation. J. Comp. Neurol. 525:676-692, 2017. © 2016 Wiley Periodicals, Inc.

Moving average template subtraction to remove stimulation artefacts in EEGs and LFPs recorded during deep brain stimulation

BackgroundDeep brain stimulation (DBS) is a well established therapy to treat movement disorders such as Parkinson's disease. More recently it has also been discussed as a therapy for certain psychiatric diseases. However, during active DBS the recordings of local field potentials (LFP) and the electroencephalogram (EEG) can be corrupted by substantial spike-type artefacts which need to be removed before any analysis. New methodHere, we present a new method that we term ' Moving Average Subtraction' (MAS) that removes DBS artefacts by subtracting adaptive DBS artefact templates from the artefact contaminated data. In particular we have developed a resampling technique which is more efficient than upsampling for a precise reconstruction of the artefact shape without the need to oversample the EEGs. ResultsBy applying this method we can derive undistorted signals even in case of the low sampling frequencies that are usual in clinical recordings. We applied the new technique to 12 data sets recorded at the surface and in various brain structures [subthalamic nucleus (STN), pedunculo pontine nucleus (PPN), Globus pallidus internus (GPi)] with 7 patients. Our results demonstrate the suppression of artefact related activity at the basic and harmonic frequencies of DBS. Comparison with existing method(s)The new technique outperforms the non-adaptive template subtraction technique for the removal of high frequency artefact residuals without producing the spectral dips that occur with notch filter approaches. ConclusionsThe new technique facilitates the analysis of higher frequency bands (Gamma activity) in LFPs and EEGs recorded during active DBS.

Learning discriminative shape statistics distribution features for pedestrian detection

Discriminative feature plays an important role in object detection system and traditional tactics heavily depends on the hand-designed feature. Recent study shows that feature can be learned from data, and this idea opens a new way to deal with many computer vision problems. In this paper, we propose a novel feature which learns discriminative information based on data distribution and shape statistics for pedestrian detection. It makes use of data distribution which is rich of discriminative information from positive and negative samples, and also utilizes shape statistics which comes from average human template. The proposed method exploits the distribution in multiple channel image spaces, and learns an optimal hyper plane to separate pedestrians from background patches in specific area with shape statistics. It maintains the merit of simplicity in computation and also obtains powerful discriminative ability. Two versions of Shape Statistic Distribution features are proposed which are derived from Informed Haar-like feature, but more discriminative than the original one. Experimental results based on INRIA, ETH and Caltech-USA datasets show that our proposed methods can achieve state-of-art performance. Furthermore the running speed of our detector can reach at 22fps for 480×640 images.

Template-free modeling by LEE and LEER in CASP11.

For the template-free modeling of human targets of CASP11, we utilized two of our modeling protocols, LEE and LEER. The LEE protocol took CASP11-released server models as the input and used some of them as templates for 3D (three-dimensional) modeling. The template selection procedure was based on the clustering of the server models aided by a community detection method of a server-model network. Restraining energy terms generated from the selected templates together with physical and statistical energy terms were used to build 3D models. Side-chains of the 3D models were rebuilt using target-specific consensus side-chain library along with the SCWRL4 rotamer library, which completed the LEE protocol. The first success factor of the LEE protocol was due to efficient server model screening. The average backbone accuracy of selected server models was similar to that of top 30% server models. The second factor was that a proper energy function along with our optimization method guided us, so that we successfully generated better quality models than the input template models. In 10 out of 24 cases, better backbone structures than the best of input template structures were generated. LEE models were further refined by performing restrained molecular dynamics simulations to generate LEER models. CASP11 results indicate that LEE models were better than the average template models in terms of both backbone structures and side-chain orientations. LEER models were of improved physical realism and stereo-chemistry compared to LEE models, and they were comparable to LEE models in the backbone accuracy. Proteins 2016; 84(Suppl 1):118-130. © 2015 Wiley Periodicals, Inc.

Stereotaxic Magnetic Resonance Imaging Brain Atlases for Infants from 3 to 12 Months

Background: Accurate labeling of brain structures within an individual or group is a key issue in neuroimaging. Methods for labeling infant brains have depended on the labels done on adult brains or average magnetic resonance imaging (MRI) templates based on adult brains. However, the features of adult brains differ in several ways from infant brains, so the creation of a labeled stereotaxic atlas based on infants would be helpful. The current work builds on the recent creation of age-appropriate average MRI templates during the first year (3, 4.5, 6, 7.5, 9, and 12 months) by creating anatomical label sets for each template. Methods: We created stereotaxic atlases for the age-specific average MRI templates. Manual delineation of cortical and subcortical areas was done on the average templates based on infants during the first year. We also applied a procedure for automatic computation of macroanatomical atlases for individual infant participants using two manually segmented adult atlases (Hammers, LONI Probabilistic Brain Atlas-LPBA40). To evaluate our methods, we did manual delineation of several cortical areas on selected individuals from each age. Linear and nonlinear registration of the individual and average template was used to transform the average atlas into the individual participant's space, and the average-transformed atlas was compared to the individual manually delineated brain areas. We also applied these methods to an external data set - not used in the atlas creation - to test generalizability of the atlases. Results: Age-appropriate manual atlases were the best fit to the individual manually delineated regions, with more error seen at greater age discrepancy. There was a close fit between the manually delineated and the automatically labeled regions for individual participants and for the age-appropriate template-based atlas transformed into participant space. There was close correspondence between automatic labeling of individual brain regions and those from the age-appropriate template. These relationships held even when tested on an external set of images. Conclusion: We have created age-appropriate labeled templates for use in the study of infant development at 6 ages (3, 4.5, 6, 7.5, 9, and 12 months). Comparison with manual methods was quite good. We developed three stereotaxic atlases (one manual, two automatic) for each infant age, which should allow more fine-grained analysis of brain structure for these populations than was previously possible with existing tools. The template-based atlases constructed in the current study are available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase).