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Results for “Automated image segmentation”

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PubMed2006

Neural consequences of sleep disordered breathing: the role of intermittent hypoxia.

Sleep disordered breathing is characterised by periodic breathing, episodes of hypoxia and repeated arousals from sleep; symptoms include excessive daytime sleepiness, impairment of memory, learning and attention. Recent evidence from animal studies suggests that both intermittent hypoxia and sleep fragmentation can independently lead to neuronal defects in the hippocampus and pre frontal cortex; areas known to be closely associated with neural processing of memory and executive function. We have previously shown that sleep disordered breathing is associated with loss of gray matter concentration within the left hippocampus (47). We have now confirmed and extended this finding in 22 right handed, newly diagnosed male patients (mean (sd): age 51.8 (15.4) yrs, apnea/hypopnea index 53.1 (14.0) events/hr, minimum nocturnal oxygen saturation 75 (8.4) %) and 17 controls matched for age and handedness. Voxel-based morphometry, an automated unbiased technique, was used to characterise changes in gray matter concentration. The magnetic resonance images were segmented and grey matter concentration determined voxel by voxel. Analysis of variance was then preformed, adjusted for overall image intensity, with age as a covariant. Additional to the deficit in the left hippocampus, we found more extensive loss of gray matter bilaterally in the parahippocampus. No additional focal lesions were seen in other brain regions. Based on our findings and data from other human and animal studies, we speculate that in patients with sleep disordered breathing intermittent hypoxia is associated with neural deficit, and further that such lesions may lead to cognitive dysfunction.

Adult↗

PubMedDate not supplied

Normalized accurate measurement of longitudinal brain change.

PURPOSE: Quantitative measurement of change in brain size and shape (e.g., to estimate atrophy) is an important current area of research. New methods of change analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method has been developed that achieves high estimation accuracy. METHOD: A fully automated method of longitudinal change analysis is presented here, which automatically segments brain from nonbrain in each image, registers the two brain images while using estimated skull images to constrain scaling and skew, and finally estimates brain surface motion by tracking surface points to subvoxel accuracy. RESULTS AND CONCLUSION: The method described has been shown to be accurate ( approximately 0.2% brain volume change error) and to achieve high robustness (no failures in several hundred analyses over a range of different data sets).

Adult↗

PubMed1992

A processing strategy for automated Papanicolaou smear screening.

A multilayer processing strategy was developed for the automatic screening of conventionally prepared Papanicolaou smears. The processing stages include image segmentation, feature extraction, object classification and slide classification. Mathematical morphology functions were implemented in hardware with custom-built gate array processors for image segmentation. There were 68 features used for classifier training. In object classification we combined the evidential supports of a binary decision tree classifier and a multilayer perceptron classifier to achieve an integrated decision. In this feasibility study, 449 conventionally prepared cervical Papanicolaou smears were tested in a prototype research system between January and May 1991. The 95% confidence interval for the slide false-negative rate was 1-9%, and the 95% confidence interval for the slide sort rate was 45-55%. The estimated sort rate for clearly normal slides is within the range required for a cost-efficient screening system, and the estimated false-negative rate for premalignant and malignant smears is an improvement over published false-negative rates for human performance. Several performance improvement efforts are still under way. We expect that they will result in a vastly reduced slide false-negative rate.

Automation↗

PubMed2005

Java Web Start based software for automated quantitative nuclear analysis of prostate cancer and benign prostate hyperplasia.

BACKGROUND: Androgen acts via androgen receptor (AR) and accurate measurement of the levels of AR protein expression is critical for prostate research. The expression of AR in paired specimens of benign prostate and prostate cancer from 20 African and 20 Caucasian Americans was compared to demonstrate an application of this system. METHODS: A set of 200 immunopositive and 200 immunonegative nuclei were collected from the images using a macro developed in Image Pro Plus. Linear Discriminant and Logistic Regression analyses were performed on the data to generate classification coefficients. Classification coefficients render the automated image analysis software independent of the type of immunostaining or image acquisition system used. The image analysis software performs local segmentation and uses nuclear shape and size to detect prostatic epithelial nuclei. AR expression is described by (a) percentage of immunopositive nuclei; (b) percentage of immunopositive nuclear area; and (c) intensity of AR expression among immunopositive nuclei or areas. RESULTS: The percent positive nuclei and percent nuclear area were similar by race in both benign prostate hyperplasia and prostate cancer. In prostate cancer epithelial nuclei, African Americans exhibited 38% higher levels of AR immunostaining than Caucasian Americans (two sided Student's t-tests; P < 0.05). Intensity of AR immunostaining was similar between races in benign prostate. CONCLUSION: The differences measured in the intensity of AR expression in prostate cancer were consistent with previous studies. Classification coefficients are required due to non-standardized immunostaining and image collection methods across medical institutions and research laboratories and helps customize the software for the specimen under study. The availability of a free, automated system creates new opportunities for testing, evaluation and use of this image analysis system by many research groups who study nuclear protein expression.

Algorithms↗

PubMed1996

Differences of regional coronary flow reserve assessed by adenosine thallium-201 scintigraphy early and six months after successful percutaneous transluminal coronary angioplasty or stent implantation.

This study assesses regional coronary flow reserve using adenosine thallium-201 scintigraphy early and 6 months after angiographically successful percutaneous transluminal coronary angioplasty (PTCA) or stent implantation. Seventeen consecutive men with a significant isolated left anterior descending coronary artery stenosis were scheduled for repeat coronary angiography and adenosine-planar thallium-201 scintigraphy within 24 hours and 6 months after successful PTCA (n = 8) or stent implantation (n = 9). After background subtraction, left ventricular segmental uptake was semiquantitatively assessed on thallium images. The perfusion defect severity was scored from 0 (normal) to 3. Coronary angiograms were analyzed using an automated edge contour detection computer analysis system. Data are expressed as mean value +/- 1 SD, and proportions as percentage. The residual narrowing was 17 +/- 8% after PTCA and 9 +/- 2% after stent implantation (p = 0.02). Twenty-four hours after the procedure, hypoperfused segments were detected in all patients (100%) and in 4 patients (44%) (p = 0.05), respectively. The total number of hypoperfused segments was greater after PTCA than after stent implantation (16 [40%] vs 7 [16%], p = 0.001, respectively) as was the perfusion defect severity (4.4 +/- 3.1 vs 1 +/- 1.2, p = 0.006). Six months after the procedure, 3 of the 5 patients who had undergone PTCA without restenosis still had reversible perfusion defects. None of the stent-treated patients had restenosis or reversible perfusion defects (p = 0.05). Among PTCA-treated patients without restenosis, the total number of hypoperfused segments and the perfusion defect severity were 9 of 25 (36%) and 0.8 +/- 0.8, respectively. Thus, a regional reduction in coronary flow reserve, occasionally observed early after successful stent implantation, is probably due to a transient alteration of small coronary vessels, as was also supported by the absence of perfusion defects 6 months after the procedure. The more severe impairment of regional coronary flow reserve observed early after successful PTCA is probably also due to angiographic underestimation of the residual stenosis, as suggested also by the persistence of reversible perfusion defects 6 months after the procedure in a few patients.

Adenosine↗

PubMed2002

Temporal classification of Drosophila segmentation gene expression patterns by the multi-valued neural recognition method.

In order to reconstruct the establishment of the body pattern over time in Drosophila embryos, we have developed automated methods for detecting the age of an embryo on the basis of knowledge about its gene expression patterns. In this paper we perform temporal classification of confocal images of expression patterns of genes controlling segmentation by means of a neural network based on multi-valued neurons (MVN). MVN are artificial neural processing elements with complex-valued weights and high functionality, which proved to be efficient for solving the image recognition problems. The results obtained by this method confirm its efficiency for image recognition and indicate that the method can detect characteristic features of expression patterns which mark their development over time.

Animals↗

PubMed2005

Towards quantitative analysis of coronary CTA.

The current high spatial and temporal resolution, multi-slice imaging capability, and ECG-gated reconstruction of multi-slice computed tomography (MSCT) allows the non-invasive 3D imaging of opacified coronary arteries. MSCT coronary angiography studies are currently carried out by the visual inspection of the degree of stenosis and it has been shown that the assessment with sensitivities and specificities of 90% and higher can be achieved. To increase the reproducibility of the analysis, we present a method that performs the quantitative analysis of coronary artery diseases with limited user interaction: only the positioning of one or two seed points is required. The method allows the segmentation of the entire left or right coronary tree by the positioning of a single seed point, and an extensive evaluation of a particular vessel segment by placing a proximal and distal seed point. The presented method consists of: (1) the segmentation of the coronary vessels, (2) the extraction of the vessel centerline, (3) the reformatting of the image volume, (4) a combination of longitudinal and transversal contour detection, and (5) the quantification of vessel morphological parameters. The method is illustrated in this paper by the segmentation of the left and right coronary trees and by the analysis of a coronary artery segment. The sensitivity of the positioning of the seed points is studied by varying the position of the proximal and distal seed points with a standard deviation of 6 and 8 mm (along the vessel's course) respectively. It is shown that only close to the individual seed points the vessel centerlines deviate and that for more than 80% of the centerlines the paths coincide. Since the quantification depends on the determination of the centerline, no user variability is expected as long as the seed points are positioned reasonably far away from the vessel lesion. The major bottleneck of MSCT imaging of the coronary arteries is the potential lack of image quality due to limitations in the spatial and temporal resolution, irregular or high heart beat, respiratory effects, and variations of the distribution of the contrast agent: the number of rejected vessel segments in diagnostic studies is currently still too high for implementation in routine clinical practice. Also for the automated quantitative analysis of the coronary arteries high image quality is required. However, based upon the trend in technological development of MSCT scanners, there is no doubt that the quantitative analysis of MSCT coronary angiography will benefit from these technological advances in the near future.

Coronary Angiography↗

PubMed1999

Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences.

Evaluating precisely the temporal variations of lesion volumes is very important for at least three types of practical applications: pharmaceutical trials, decision making for drug treatment or surgery, and patient follow-up. In this paper we present a volumetric analysis technique, combining precise rigid registration of three-dimensional (3-D) (volumetric) medical images, nonrigid deformation computation, and flow-field analysis. Our analysis technique has two outcomes: the detection of evolving lesions and the quantitative measurement of volume variations. The originality of our approach is that no precise segmentation of the lesion is needed but the approximative designation of a region of interest (ROI) which can be automated. We distinguish between tissue transformation (image intensity changes without deformation) and expansion or contraction effects reflecting a change of mass within the tissue. A real lesion is generally the combination of both effects. The method is tested with synthesized volumetric image sequences and applied, in a first attempt to quantify in vivo a mass effect, to the analysis of a real patient case with multiple sclerosis (MS).

Algorithms↗

PubMed1989

Measurement of absolute flow rate in vessels using a stereoscopic DSA system.

We used a stereoscopic digital subtraction angiography (DSA) system to measure absolute blood flow rates in vessels. The magnification factor and the three-dimensional orientation of a selected vessel are obtained from automated analysis of stereoscopic DSA images. The cross-sectional area of the vessel is determined from the vessel diameter, which is measured with an iterative deconvolution technique. The time required for fluid to flow through a selected segment of a vessel is determined from the automated analysis of contrast medium 'time-density' curves. The effectiveness of these combined techniques was demonstrated in measurement of rates of both continuous and pulsatile flow in a vessel phantom, with the actual flow rate calibrated volumetrically or by an electromagnetic flowmeter. We have obtained accuracies in measured flow rates of approximately 5% and 18% for continuous and pulsatile flow respectively.

Angiography↗

PubMed1999

Geometric vascular remodeling after balloon angioplasty and beta-radiation therapy: A three-dimensional intravascular ultrasound study.

BACKGROUND: Endovascular radiation appears to inhibit intimal thickening after overstretching balloon injury in animal models. The effect of brachytherapy on vascular remodeling is unknown. The aim of the study was to determine the evolution of coronary vessel dimensions after intracoronary irradiation after successful balloon angioplasty in humans. METHODS AND RESULTS: Twenty-one consecutive patients treated with balloon angioplasty and beta-radiation according to the Beta Energy Restenosis Trial-1.5 were included in the study. Volumetric assessment of the irradiated segment and both edges was performed after brachytherapy and at 6-month follow-up. Intravascular ultrasound images were acquired by means of ECG-triggered pullback, and 3-D reconstruction was performed by automated edge detection, allowing the calculation of lumen, plaque, and external elastic membrane (EEM) volumes. In the irradiated segments, mean EEM and plaque volumes increased significantly (451+/-128 to 490.9+/-159 mm(3) and 201.2+/-59 to 241.7+/-74 mm(3); P=0.01 and P=0.001, respectively), whereas luminal volume remained unchanged (250.8+/-91 to 249.2+/-102 mm(3); P=NS). The edges demonstrated an increase in mean plaque volume (26.8+/-12 to 32. 6+/-10 mm(3), P=0.0001) and no net change in mean EEM volume (71. 4+/-24 to 70.9+/-24 mm(3), P=NS), resulting in a decrease in mean luminal volume (44.6+/-16 to 38.3+/-16 mm(3), P=0.01). CONCLUSIONS: A different pattern of remodeling is observed in coronary segments treated with beta-radiation after successful balloon angioplasty. In the irradiated segments, the adaptive increase of EEM volume appears to be the major contributor to the luminal volume at follow-up. Conversely, both edges showed an increase in plaque volume without a net change in EEM volume.

Angioplasty, Balloon↗

PubMed1998

Automated segmentation of anatomic regions in chest radiographs using an adaptive-sized hybrid neural network.

The purposes of this research are to investigate the effectiveness of our novel image features for segmentation of anatomic regions such as the lungs and the mediastinum in chest radiographs and to develop an automatic computerized method for image processing. A total of 85 screening chest radiographs from Johns Hopkins University Hospital were digitized to 2 K by 2.5 K pixels with 12 bit gray scale. To reduce the amount of information, the images were smoothed and subsampled to 256 by 310 pixels with 8 bit. The determination approach consists of classifying each pixel into two anatomic classes (lung and others) on the basis of several image features: (1) relative pixel address (Rx, Ry) based on lung edges extracted through image processing using profile, (2) density normalized from lungs and mediastinum density, and (3) histogram equalized entropy. The combinations of image features were evaluated using an adaptive-sized hybrid neural network consisting of an input, a hidden, and an output layer. Fourteen images were used for the training of the neural network and the remaining 71 images for testing. Using four features of relative address (Rx, Ry), normalized density, and histogram equalized entropy, the neural networks classified lungs at 92% accuracy against test images following the same rules as for the training images.

Biophysical Phenomena↗

PubMed2006

Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI.

PURPOSE: To automatically segment multiple sclerosis (MS) lesions into three subtypes (i.e., enhancing lesions, T1 "black holes", T2 hyperintense lesions). MATERIALS AND METHODS: Proton density-, T2- and contrast-enhanced T1-weighted brain images of 12 MR scans were pre-processed through intracranial cavity (IC) extraction, inhomogeneity correction and intensity normalization. Intensity-based statistical k-nearest neighbor (k-NN) classification was combined with template-driven segmentation and partial volume artifact correction (TDS+) for segmentation of MS lesions subtypes and brain tissue compartments. Operator-supervised tissue sampling and parameter calibration were performed on 2 randomly selected scans and were applied automatically to the remaining 10 scans. Results from this three-channel TDS+ (3ch-TDS+) were compared to those from a previously validated two-channel TDS+ (2ch-TDS+) method. The results of both the 3ch-TDS+ and 2ch-TDS+ were also compared to manual segmentation performed by experts. RESULTS: Intra-class correlation coefficients (ICC) of 3ch-TDS+ for all three subtypes of lesions were higher (ICC between 0.95 and 0.96) than that of 2ch-TDS+ for T2 lesions (ICC = 0.82). The 3ch-TDS+ also identified the three lesion subtypes with high specificity (98.7-99.9%) and accuracy (98.5-99.9%). Sensitivity of 3ch-TDS+ for T2 lesions was 16% higher than with 2ch-TDS+. Enhancing lesions were segmented with the best sensitivity (81.9%). "Black holes" were segmented with the least sensitivity (62.3%). CONCLUSION: 3ch-TDS+ is a promising method for automated segmentation of MS lesion subtypes.

Adult↗

PubMed2003

Neuron recognition by parallel Potts segmentation.

Identifying neurons and their spatial coordinates in images of the cerebral cortex is a necessary step in the quantitative analysis of spatial organization in the brain. This is especially important in the study of Alzheimer's disease (AD), in which spatial neuronal organization and relationships are highly disrupted because of neuronal loss. To automate neuron recognition by using high-resolution confocal microscope images from human brain tissue, we propose a recognition method based on statistical physics that consists of image preprocessing, parallel image segmentation, and cluster selection on the basis of shape, optical density, and size. We segment a preprocessed digital image into clusters by applying Monte Carlo simulations of a q-state inhomogeneous Potts model. We then select the range of Potts segmentation parameters to yield an ideal recognition of simplified objects in the test image. We apply our parallel segmentation method to control individuals and to AD patients and achieve recognition of 98% (for a control) and 93% (for an AD patient), with at most 3% false clusters.

Alzheimer Disease↗

PubMed1994

Presentation of colour flow maps of the peripheral circulation.

The use of continuous wave Doppler ultrasound for lower limb arterial assessment is a well established technique in most district hospitals. Patients found to have disturbances in blood flow attributable to arterial plaques are often referred for arteriographic visualization of the disease with its inherent risks and complications. The availability of colour flow mapping on modern ultrasound scanners provides a non-invasive way of detecting the size and extent of these plaques and, in some institutions, is replacing arteriography. One possible disadvantage of the use of colour flow mapping is that it does not provide a permanent record showing the relationship of the plaques to the patient's gross anatomy in the same way as arteriography. This may limit the acceptability of this technique. At Lincoln work was undertaken to develop a system for presenting images of a whole segment of a limb simultaneously along with the associated blood velocity spectrum. This was performed first by hand and then a suite of computer software was developed to automate the process. Comparisons were made between the ultrasound based images and arteriography, showing the techniques to be of similar diagnostic value. The technique provides composite images showing anatomical detail, blood flow and velocity spectra for ease of interpretation. Further studies will be undertaken in order to define patient groups where diagnostic arteriography can be avoided.

Color↗

PubMed2003

Image registration via level-set motion: applications to atlas-based segmentation.

Image registration is an often encountered problem in various fields including medical imaging, computer vision and image processing. Numerous algorithms for registering image data have been reported in these areas. In this paper, we present a novel curve evolution approach expressed in a level-set framework to achieve image intensity morphing and a simple non-linear PDE for the corresponding coordinate registration. The key features of the intensity morphing model are that (a) it is very fast and (b) existence and uniqueness of the solution for the evolution model are established in a Sobolev space as opposed to using viscosity methods. The salient features of the coordinate registration model are its simplicity and computational efficiency. The intensity morph is easily achieved via evolving level-sets of one image into the level-sets of the other. To explicitly estimate the coordinate transformation between the images, we derive a non-linear PDE-based motion model which can be solved very efficiently. We demonstrate the performance of our algorithm on a variety of images including synthetic and real data. As an application of the PDE-based motion model, atlas based segmentation of hippocampal shape from several MR brain scans is depicted. In each of these experiments, automated hippocampal shape recovery results are validated via manual "expert" segmentations.

Adult↗

PubMed1998

Serial volumetric (three-dimensional) intravascular ultrasound analysis of restenosis after directional coronary atherectomy.

OBJECTIVES: We report the use of three-dimensional (volumetric) intravascular ultrasound (IVUS) analysis to assess serial changes after directional coronary atherectomy (DCA). BACKGROUND: Recent serial planar IVUS studies have described a decrease in external elastic membrane (EEM) area following catheter-based intervention as an important mechanism of late lumen renarrowing. METHODS: Thirty-one patients with de novo native coronary lesions treated with DCA in the Serial Ultrasound Restenosis (SURE) Trial and in Optimal Atherectomy Restenosis Study (OARS) were enrolled in this study. Serial IVUS was performed before and after intervention and at 6 months' follow-up. In a subgroup of 18 patients from the SURE trial, IVUS was also performed at 24 h and at 1 month postintervention. Segments, 20-mm-long (200 image slices), were analyzed using a previously validated three-dimensional, computerized, automated edge-detection algorithm. The EEM, lumen, and plaque+media (P+M = EEM-lumen) volumes were calculated. RESULTS: At follow-up, lumen volume was smaller than at postintervention (159+/-69 mm3 vs. 179+/-49 mm3, p = 0.0003). From postintervention to follow-up, there was a decrease in EEM volume (377+/-107 to 352+/-125 mm3, p < 0.0001), but no change in P+M volume (p = 0.52). The delta lumen volume correlated strongly with deltaEEM volume (r = 0.842, p < 0.0001), but not with deltaP+M volume. In the 18 patients from the SURE Trial, the decrease in lumen and EEM volumes occurred late, between 1 month and 6 months of follow-up. CONCLUSIONS: Volumetric IVUS analysis demonstrated that late lumen volume loss following DCA was a result of a decrease in EEM volume. This was a late event, occurring between 1 and 6 months' postintervention.

Aged↗

PubMed2000

T-snakes: topology adaptive snakes.

We present a new class of deformable contours (snakes) and apply them to the segmentation of medical images. Our snakes are defined in terms of an affine cell image decomposition (ACID). The 'snakes in ACID' framework significantly extends conventional snakes, enabling topological flexibility among other features. The resulting topology adaptive snakes, or 'T-snakes', can be used to segment some of the most complex-shaped biological structures from medical images in an efficient and highly automated manner.

Brain↗

PubMed2004

Integration of biochemical images of a tumor into frameless stereotaxy achieved using a magnetic resonance imaging/magnetic resonance spectroscopy hybrid data set.

OBJECT: It is often difficult to delineate the extent of invasion of high- and low-grade gliomas into normal brain tissue by using conventional T1- and T2-weighted magnetic resonance (MR) imaging. Knowledge of the relationship between the tumor infiltration zone and normal brain, however, is one of the prerequisites for performing as radical a tumor resection as possible. Proton MR spectroscopy allows noninvasive measurements of the concentrations and spatial distributions of brain metabolites and, therefore, may provide biochemical information in vivo, that is useful in distinguishing pathological from normal areas of the brain. The authors have developed a method to use the properties of MR spectroscopy to investigate intraoperatively pathological changes in the spatial distribution of choline (Cho)-containing compounds, total creatine, and N-acetylaspartate (NAA) in brain tumors with the aid of frameless stereotaxy. METHODS: Maps of the Cho/NAA ratio were calculated and automatic segmentation of the tumors was performed. Spectroscopic images of the segmented tumor were matched to an anatomical three-dimensional (3D) MR imaging set by applying a fully automated mutual-information algorithm. The resulting 3D MR image can be used subsequently for neurosurgical planning, transfer to a frameless stereotactic system, and display in the navigation microscope during surgery leading to 1H-MR spectroscopy-guided navigation. CONCLUSIONS: This method may allow better intraoperative identification of tumor border zones based on metabolic changes due to tumor infiltration.

Brain Neoplasms↗