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PubMed2005

Automatic morphometry of synaptic boutons of cultured cells using granulometric analysis of digital images.

Numbers, linear density, and surface area of synaptic boutons can be important parameters in studies on synaptic plasticity in cultured neurons. We present a method for automatic identification and morphometry of boutons based on filtering of digital images using granulometric analysis. Cultures of cortical neurons (DIV8 and DIV21) were fixed and marked with fluorescently labeled antibodies for synapsin I (a marker for synaptic boutons) and MAP-2 (a marker for dendrites). Images were acquired on a confocal microscope and automatically processed. Granulometry, a morphological operator sensitive to the geometry and size of objects, was used to construct a filter passing fuzzy fluorescent grains of a certain size. Next, the filter was overlaid with the original image (masking) and the positive pixels were identified by an integral intensity threshold (thresholding). Disjoint grains, representing individual boutons, were reconstructed from the connected pixels above the threshold, numbered and their area was measured. In total, 1498 boutons with a mean diameter of 1.63 +/- 0.49 microm (S.D.) were measured. Comparisons with manual counts showed that the proposed method was capable of identifying boutons in a systematic manner at the light microscopic level and was a viable alternative to manual bouton counting.

Algorithms↗
PubMed2006

A new multi-electrode array design for chronic neural recording, with independent and automatic hydraulic positioning.

We report on a new microdrive design, which enables the construction of multi-electrode arrays capable of chronically recording the multi-unit neural activity of waking animals. Our principal motivation for inventing this device was to simplify the task of positioning electrodes, which consumes a considerable amount of time and requires a high level of skill. With the new microdrives, each electrode is independently and automatically driven into place. A hydraulic drive system is adopted to reduce the size, weight, and cost of the structure. The hydraulic fluid is also used as a part of the electrical circuit, and facilitates the wiring of the electrodes. A routing system has been attached to reduce the number of tube connections. The microdrive is cylindrical, has a diameter of 23.5 mm, a height of 37 mm, and a weight of 15 g. It allows for up to 22 electrodes, which are arranged on a 0.35 mm grid. Each electrode can be positioned at any depth up to approximately 4mm. The microdrive was evaluated under acute and chronic recording experiments, and is shown to be capable of automatically positioning each electrode and successfully recording the neural signals of waking rats.

Animals↗
PubMedDate not supplied

Fast automatic particle picking from cryo-electron micrographs using a locally normalized cross-correlation function: a case study.

Recent progress in single-particle reconstruction methods and cryo-EM techniques has led to the determination of macromolecular structures with unprecedented resolution. The number of particles that goes into the reconstruction is a key determinant in achieving high resolution. Interactive manual picking of particles from an electron micrograph is a very time-consuming, tedious, and inefficient process. We have implemented a fast automatic particle picking procedure in the SPIDER environment. The procedure makes use of template matching schemes and employs a recently developed locally normalized correlation algorithm based on Fourier techniques. As a test, we have used this procedure to pick 70S Escherichia coli ribosomes from a cryo-electron micrograph. Different search strategies including use of a circular mask and asymmetric masks for different orientations of the particle have been explored, and their relative efficiencies are discussed. The results indicate that the procedure can be optimally used to pick ribosomes in a fully automatic way within the limit of selecting less than 10% false positives while missing about 15% of true positives.

Algorithms↗
PubMed2004

Auto-accumulation method using simulated annealing enables fully automatic particle pickup completely free from a matching template or learning data.

Single-particle analysis is a 3-D structure determining method using electron microscopy (EM). In this method, a large number of projections is required to create 3-D reconstruction. In order to enable completely automatic pickup without a matching template or a training data set, we established a brand-new method in which the frames to pickup particles are randomly shifted and rotated over the electron micrograph and, using the total average image of the framed images as an index, each frame reaches a particle. In this process, shifts are selected to increase the contrast of the average. By iterated shifts and further selection of the shifts, the frames are induced to shift so as to surround particles. In this algorithm, hundreds of frames are initially distributed randomly over the electron micrograph in which multi-particle images are dispersed. Starting with these frames, one of them is selected and shifted randomly, and acceptance or non-acceptance of its new position is judged using the simulated annealing (SA) method in which the contrast score of the total average image is adopted as an index. After iteration of this process, the position of each frame converges so as to surround a particle and the framed images are picked up. This method is the first unsupervised fully automatic particle picking method which is applicable to EM of various kinds of proteins, especially to low-contrasted cryo-EM protein images.

Algorithms↗
PubMed2005

Model structures of alpha-2 adrenoceptors in complex with automatically docked antagonist ligands raise the possibility of interactions dissimilar from agonist ligands.

Antagonist binding to alpha-2 adrenoceptors (alpha2-ARs) is not well understood. Structural models were constructed for the three human alpha2-AR subtypes based on the bovine rhodopsin X-ray structure. Twelve antagonist ligands (including covalently binding phenoxybenzamine) were automatically docked to the models. A hallmark of agonist binding is the electrostatic interaction between a positive charge on the agonist and the negatively charged side chain of D3.32. For antagonist binding, ion-pair formation would require deviations of the models from the rhodopsin structural template, e.g., a rotation of TM3 to relocate D3.32 more centrally within the binding cavity, and/or creation of new space near TM2/TM7 such that antagonists would be shifted away from TM5. Thus, except for the quinazolines, antagonist ligands automatically docked to the model structures did not form ion-pairs with D3.32. This binding mode represents a valid alternative, whereby the positive charge on the antagonists is stabilized by cation-pi interactions with aromatic residues (e.g., F6.51) and antagonists interact with D3.32 via carboxylate-aromatic interactions. This binding mode is in good agreement with maps derived from a molecular interaction library that predicts favorable atomic contacts; similar interaction environments are seen for unrelated proteins in complex with ligands sharing similarities with the alpha2-AR antagonists.

Adrenergic alpha-2 Receptor Agonists↗
PubMed2006

A fully automatic 3D reconstruction method using simulated annealing enables accurate posterioric angular assignment of protein projections.

Single-particle analysis is a structure determining method using electron microscopic (EM) images, which does not require protein crystal. In this method, projections are picked up and used to reconstruct a three-dimensional (3D) structure. When the conical tilting method is not available, the particle images are usually classified and averaged to improve the signal-to-noise ratio. The Euler angles of these average images must be posteriorically assigned to create a primary 3D model. We developed a new, fully automatic unsupervised Euler angle assignment method, which does not require an initial 3D reference and which is applicable to asymmetric molecules. In this method, the Euler angle of each average image is initially set randomly and then automatically corrected in relation to those of the other averages by iterated optimizations using the Simulated Annealing (SA) algorithm. At each iteration, the 3D structure is reconstructed based on the current Euler angles and reprojected back in the average-input directions. A modified cross-correlation between each reprojection and its corresponding original average is then calculated. The correlations are summed as a total 3D echo-correlation score to evaluate the Euler angles at this iteration. Then, one of the projections is selected, its Euler angle is changed randomly, and the score is also calculated. Based on the score change, judgment of whether to accept or reject the new angle is made using the SA algorithm, which is introduced to overcome the local minimums. After a certain number of iterations of this process, the angles of all averages converge so as to create a reliable primary 3D model. This echo-correlated 3D reconstruction with simulated annealing also has potential for wide application to general 3D reconstruction from various types of 2D images.

Algorithms↗
PubMed2005

Automatic quantitation of vacuolar lesions in the brain of mice infected with transmissible spongiform encephalopathies.

The spongiform change induced in the brain tissue is one of the major features investigated in the neuropathology in natural and experimental transmissible spongiform encephalopathies (TSEs). In this context, a reproducible quantitation of the magnitude of these vacuolar lesions is described using image analysis techniques. To be exploited successfully, this image analysis must be able to distinguish the vacuolar lesions from vascular elements. The present study describes the different calibration stages of image analysis using hematoxylin-eosin stained slices of brain from mice infected with TSEs. In order to select automatically a maximum of vacuoles and to eliminate a maximum of vascular elements, relevant criteria based on the threshold values of the optical density, shape factor and surface of detected objects were determined. Compared to visual scoring, this method has the advantages of enhanced precision of the measure, reproducibility and moreover, the collection of numerical data for more detailed statistical analysis. In addition, an original scale change function is proposed allowing a comparative analysis with values from the visual scoring method. The method of automatic recognition and quantitation of vacuolar lesions described in this paper represent a useful tool for large-scale analysis of spongiform lesions induced by different TSE isolates transmitted to mice.

Animals↗
PubMed2005

Automatic navigation path generation based on two-phase adaptive region-growing algorithm for virtual angioscopy.

In this paper, we propose a fast and automated navigation path generation algorithm to visualize inside of carotid artery using MR angiography images. The carotid artery is one of the body regions not accessible by real optical probe but can be visualized with virtual endoscopy. By applying two-phase adaptive region-growing algorithm, the carotid artery segmentation is started at the initial seed, which is located on the initially thresholded binary image. This segmentation algorithm automatically detects the branch position with stack feature. Combining with a priori knowledge of anatomic structure of carotid artery, the detected branch position is used to separate the carotid artery into internal carotid artery and external carotid artery. A fly-through path is determined to automatically move the virtual camera based on the intersecting coordinates of two bisectors on the circumscribed quadrangle of segmented carotid artery. In consideration of the interactive rendering speed and the usability of standard graphic hardware, endoscopic view of carotid artery is generated by using surface rendering algorithm with perspective projection method. In addition, the endoscopic view is provided with ray casting algorithm for off-line navigation of carotid artery. Experiments have been conducted on both mathematical phantom and clinical data sets. This algorithm is more effective than key-framing and topological thinning method in terms of automated features and computing time. This algorithm is also applicable to generate the centerline of renal artery, coronary artery, and airway tree which has tree-like cylinder shape of organ structures in the medical imagery.

Algorithms↗
PubMed2006

Automatic correction of artifact from single-trial event-related potentials by blind source separation using second order statistics only.

Event-related potentials (ERP) are in general masked by various kinds of artifacts. To attenuate the effects of artifacts, various schemes have been introduced, such as epoch rejection, electro-oculogram (EOG) regression and independent component analysis (ICA). However, none of the existing techniques can automatically remove various kinds of artifacts from a single ERP epoch. EOG regression cannot handle artifacts other than ocular ones. ICA incorporating higher order statistics (HOS) normally requires data with large number of time samples in order that the solution is robust. In this paper we blindly separate the multi-channel ERP into source components by estimating the correlation matrices of the data. Since only second order statistics (SOS) is involved, the process performs well at the single epoch level. Automatic artifact identification is performed in the source domain by introducing objective criteria for various artifacts. Criteria are based on time domain signal amplitude for blink and spurious peak artifact, scalp distribution of signal power for eye movement artifact and power distribution of frequency components for muscle artifact. The correction procedure can be completed by removing the identified artifactual sources from the raw multi-channel ERP.

Algorithms↗
PubMed2006

A control system for automatic electrical stimulation of abdominal muscles to assist respiratory function in tetraplegia.

People with tetraplegia have poor respiratory function leading to limited tidal volume (V(T)) and reduced cough peak flow (CPF). These problems may cause respiratory failure during the initial admission or subsequent intercurrent illness. Electrical stimulation of the abdominal muscles during expiration can improve respiratory function by increasing V(T) and CPF. We developed a novel control system to automatically trigger muscle stimulation, synchronised with the subject's voluntary respiratory activity. The system was tested in four subjects with a functionally complete lesion at level C4 to C6, aged between 16 and 46 years, 3 months to 5 years post injury, who were breathing spontaneously. The algorithm delivered automatic stimulation patterns, detecting cough and quiet breathing while suppressing stimulation during other activities such as speaking. Marked increases in V(T) (between 9% and 71% of baseline) and CPF (between 31% and 54% of baseline) were observed, suggesting that the technique may have potential use in both acute and established tetraplegia to increase minute ventilation and to improve cough clearance of secretions.

Abdominal Muscles↗
PubMed2005

Automatic segmentation of MR images of the developing newborn brain.

This paper describes an automatic tissue segmentation method for newborn brains from magnetic resonance images (MRI). The analysis and study of newborn brain MRI is of great interest due to its potential for studying early growth patterns and morphological changes in neurodevelopmental disorders. Automatic segmentation of newborn MRI is a challenging task mainly due to the low intensity contrast and the growth process of the white matter tissue. Newborn white matter tissue undergoes a rapid myelination process, where the nerves are covered in myelin sheathes. It is necessary to identify the white matter tissue as myelinated or non-myelinated regions. The degree of myelination is a fractional voxel property that represents regional changes of white matter as a function of age. Our method makes use of a registered probabilistic brain atlas. The method first uses robust graph clustering and parameter estimation to find the initial intensity distributions. The distribution estimates are then used together with the spatial priors to perform bias correction. Finally, the method refines the segmentation using training sample pruning and non-parametric kernel density estimation. Our results demonstrate that the method is able to segment the brain tissue and identify myelinated and non-myelinated white matter regions.

Aging↗
PubMed2006

Automatic rib segmentation and labeling in computed tomography scans using a general framework for detection, recognition and segmentation of objects in volumetric data.

A system for automatic segmentation and labeling of the complete rib cage in chest CT scans is presented. The method uses a general framework for automatic detection, recognition and segmentation of objects in three-dimensional medical images. The framework consists of five stages: (1) detection of relevant image structures, (2) construction of image primitives, (3) classification of the primitives, (4) grouping and recognition of classified primitives and (5) full segmentation based on the obtained groups. For this application, first 1D ridges are extracted in 3D data. Then, primitives in the form of line elements are constructed from the ridge voxels. Next a classifier is trained to classify the primitives in foreground (ribs) and background. In the grouping stage centerlines are formed from the foreground primitives and rib numbers are assigned to the centerlines. In the final segmentation stage, the centerlines act as initialization for a seeded region growing algorithm. The method is tested on 20 CT-scans. Of the primitives, 97.5% is classified correctly (sensitivity is 96.8%, specificity is 97.8%). After grouping, 98.4% of the ribs are recognized. The final segmentation is qualitatively evaluated and is very accurate for over 80% of all ribs, with slight errors otherwise.

Algorithms↗
PubMed2006

Use of Autostitch for automatic stitching of microscope images.

Image stitching is the process of combining multiple images to produce a panorama or larger image. In many biomedical studies, including those of cancer and infection, the use of this approach is highly desirable in order to acquire large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we describe the application of Autostitch, viz. software that is normally used for the generation of panoramas in photography, in the seamless stitching of microscope images. First, we tested this software on image sets manually acquired by normal light microscopy and compared the performance with a manual stitching approach performed with Paint Shop Pro. Secondly, this software was applied to an image stack acquired by an automatic microscope. The stitching results were then compared with that generated by a self-programmed rectangular tiling macro integrated in Image J. Thirdly, this program was applied in the image stitching of images from electron microscopy. Thus, the automatic stitching program described here may find applications in convenient image stitching and virtual microscopy in the biomedical research.

Animals↗
PubMed2004

Realignment of myocardial first-pass MR perfusion images using an automatic detection of the heart-lung interface.

Magnetic resonance first-pass imaging of a bolus of contrast agent is well adapted to distinguish normal and hypoperfused areas of the myocardium. In most cases, the signal intensity-time curves in user defined regions of interest (ROI) are studied. As image acquisition is ECG-gated, the images are acquired at the same moment in the cardiac cycle, and the basic shape of the heart is similar from one view to the next. However, superficial respiratory motion can displace the heart in the short-axis plane. The aim of this study is to correct for the respiratory motion of the heart by performing an automatic realignment of the myocardial ROI based on a method tracking the movement of the lung-myocardium interface. Visual and quantitative analyses performed on 120 curves show a very good concordance between two automatic methods and the manual one.

Adult↗
PubMed2006

CORSICA: correction of structured noise in fMRI by automatic identification of ICA components.

When applied to functional magnetic resonance imaging (fMRI) data, spatial independent component analysis (sICA), a data-driven technique that addresses the blind source separation problem, seems able to extract components specifically related to physiological noise and brain movements. These components should be removed from the data to achieve structured noise reduction and improve any subsequent detection and analysis of signal fluctuations related to neural activity. We propose a new automatic method called CORSICA (CORrection of Structured noise using spatial Independent Component Analysis) to identify the components related to physiological noise, using prior information on the spatial localization of the main physiological fluctuations in fMRI data. As opposed to existing spectral priors, which may be subject to aliasing effects for long-TR data sets (typically acquired with TR >1 s), such spatial priors can be applied to fMRI data, regardless of the TR of the acquisitions. By comparing the proposed automatic selection to a manual selection performed visually by a human operator, we first show that CORSICA is able to identify the noise-related components for long-TR data with a high sensitivity and a specificity of 1. On short-TR data sets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in the gray matter, while preserving the main fluctuations related to neural activity.

Biometry↗
PubMed2003

A rapid algorithm for robust and automatic extraction of the midsagittal plane of the human cerebrum from neuroimages based on local symmetry and outlier removal.

A rapid algorithm for robust, accurate, and automatic extraction of the midsagittal plane (MSP) of the human cerebrum from normal and pathological neuroimages is proposed. The MSP is defined as a plane formed from the interhemispheric fissure line segments having the dominant orientation. The algorithm extracts the MSP in four steps: (1) determine suitable axial slices for processing, (2) localize the fissure line segments on them, (3) select inliers from the extracted fissure line segments through histogram-based outlier removal, and (4) calculate the equation of the MSP from the selected inliers. The fissure line segments are localized by minimizing the local symmetry index characterizing anatomical properties of images in the vicinity of the interhemispheric fissure. A two-stage angular and distance outlier removal is introduced to handle abnormalities. The algorithm has been validated quantitatively with 125 structural MRI and CT cases from 10 centers on three continents by studying its accuracy; tolerance to rotation, noise, asymmetry, and bias field; sensitivity to parameters; and performance. A statistical relationship between algorithm accuracy and the data's adherence to planarity is also determined. The algorithm extracts the MSP below 6 s on Pentium 4 (2.4 GHz) with the average angular and distance errors of (0.40 degrees; 0.63 mm) for normal and (0.59 degrees; 0.73 mm) for pathological cases. The robustness to noise, asymmetry, rotation, and bias field is achieved by extracting the MSP based on the dominant orientation and local symmetry index. A low computational cost results from applying simple operations capturing intrinsic anatomic features, constraining the searching space to the local vicinity of the interhemispheric fissure, and formulating a noniterative algorithm with a coarse and fine fixed-step searching. In comparison to the existing methods, our algorithm is much faster, performs accurately and robustly for a wide range of diversified data, and is fully automatic and thoroughly validated, which make it suitable for clinical applications.

Acoustic Stimulation↗
PubMed2004

MR-based automatic delineation of volumes of interest in human brain PET images using probability maps.

The purpose of this study was to develop and validate an observer-independent approach for automatic generation of volume-of-interest (VOI) brain templates to be used in emission tomography studies of the brain. The method utilizes a VOI probability map created on the basis of a database of several subjects' MR-images, where VOI sets have been defined manually. High-resolution structural MR-images and 5-HT(2A) receptor binding PET-images (in terms of (18)F-altanserin binding) from 10 healthy volunteers and 10 patients with mild cognitive impairment were included for the analysis. A template including 35 VOIs was manually delineated on the subjects' MR images. Through a warping algorithm template VOI sets defined from each individual were transferred to the other subjects MR-images and the voxel overlap was compared to the VOI set specifically drawn for that particular individual. Comparisons were also made for the VOI templates 5-HT(2A) receptor binding values. It was shown that when the generated VOI set is based on more than one template VOI set, delineation of VOIs is better reproduced and shows less variation as compared both to transfer of a single set of template VOIs as well as manual delineation of the VOI set. The approach was also shown to work equally well in individuals with pronounced cerebral atrophy. Probability-map-based automatic delineation of VOIs is a fast, objective, reproducible, and safe way to assess regional brain values from PET or SPECT scans. In addition, the method applies well in elderly subjects, even in the presence of pronounced cerebral atrophy.

Aged↗
PubMed2005

On-line automatic slice positioning for brain MR imaging.

In clinical brain MR imaging protocols, the technician collects a quick localizer and manually positions the subsequent scans using the localizer as a guide. We present a method for automatic slice positioning using a rapidly acquired 3D localizer. The localizer is automatically aligned to a statistical atlas representing 40 healthy subjects. The atlas contains the probability of a given tissue type occurring at a given location in atlas space and the conditional probability distribution of the multi-spectral MRI intensity values for a given tissue class. Accurate rigid alignment of each subject to an atlas ensures that all patients' scans are acquired in a consistent manner. A further benefit is that slices are positioned consistently over time, so that scans of patients returning for follow-up imaging can be compared side-by-side to accurately monitor the progression of illness. The procedure also helps ensure that left/right asymmetries reflect true anatomy rather than being the result of oblique slice positioning relative to the underlying anatomy. The use of an atlas-based procedure eliminates the need to refer to a database of previously scanned images of the same patient and ensures corresponding alignment across scanners and sites, without requiring fiducial markers. Since the registration method is probabilistic, the registration error tends to increase smoothly in the presence of increasing noise and unusual anatomy or pathology rather than failing catastrophically. Translations and rotations relative to the atlas can be set so that planning can be done in anatomical space, rather than scanner coordinates, and stored as part of the protocol allowing standardization of slice orientations.

Algorithms↗