Automated identification of minimal myocardial motion for improved image quality on MR angiography at 3 T

OBJECTIVE: Imaging during a period of minimal myocardial motion is of paramount importance for coronary MR angiography (MRA). The objective of our study was to evaluate the utility of FREEZE, a custom-built automated tool for the identification of the period of minimal myocardial motion, in both a moving phantom at 1.5 T and 10 healthy adults (nine men, one woman; mean age, 24.9 years; age range, 21-32 years) at 3 T. CONCLUSION: Quantitative analysis of the moving phantom showed that dimension measurements approached those obtained in the static phantom when using FREEZE. In vitro, vessel sharpness, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were significantly improved when coronary MRA was performed during the software-prescribed period of minimal myocardial motion (p < 0.05). Consistent with these objective findings, image quality assessments by consensus review also improved significantly when using the automated prescription of the period of minimal myocardial motion. The use of FREEZE improves image quality of coronary MRA. Simultaneously, operator dependence can be minimized while the ease of use is improved.

"Soap-Bubble" visualization and quantitative analysis of 3D coronary magnetic resonance angiograms.

In order to compare coronary magnetic resonance angiography (MRA) data obtained with different scanning methodologies, adequate visualization and presentation of the coronary MRA data need to be ensured. Furthermore, an objective quantitative comparison between images acquired with different scanning methods is desirable. To address this need, a software tool ("Soap-Bubble") that facilitates visualization and quantitative comparison of 3D volume targeted coronary MRA data was developed. In the present implementation, the user interactively specifies a curved subvolume (enclosed in the 3D coronary MRA data set) that closely encompasses the coronary arterial segments. With a 3D Delaunay triangulation and a parallel projection, this enables the simultaneous display of multiple coronary segments in one 2D representation. For objective quantitative analysis, frequently explored quantitative parameters such as signal-to-noise ratio (SNR); contrast-to-noise ratio (CNR); and vessel length, sharpness, and diameter can be assessed. The present tool supports visualization and objective, quantitative comparisons of coronary MRA data obtained with different scanning methods. The first results obtained in healthy adults and in patients with coronary artery disease are presented.

The development of a Flanders Interaction Analysis style instrument for use in educational computer mediated communication research

Please consult the paper edition of this thesis to read. It is available on the 5th Floor of the Library at Call Number: Z 9999 E38 D56 1992

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data

We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Spontaneous eye blink analysis in the normal individual

Purpose: Spontaneous eye blink activity in the primary eye position and its relationship to age and gender were assessed using digital image processing techniques to quantify blink opening and closing time. Methods: One hundred-and-eighty healthy volunteers (90 males and 90 females), divided into the age groups 0-3, 4-12, 13-20, 21-40, 41-60 and ≥60 years old, were evaluated prospectively. They were videotaped digitally in a standard setting and the images were transferred to a personal computer (Macintosh 400) and processed with the iMovie software. Blink opening and closing time were measured at 30 frames/second. The data were then subjected to statistical analysis. Results: The closing time was significantly longer than the opening time for all ages and both genders. Elderly individuals (≥41 years old) and women had significantly longer closing times. Conclusion: Image processing techniques made possible the observation of differences in spontaneous eye blink opening and closing time in relation to age and gender. Copyright © 2005 Taylor & Francis LLC.

Measurement of sealant surface area by clinical/computerized analysis: 11-year results.

OBJECTIVE: To analyze the clinical behavior of 2 pit and fissure sealants through clinical/computerized evaluation. METHOD AND MATERIALS: Occlusal sealants were placed on maxillary and mandibular first and second premolars according to a split-mouth design. All premolars were sealed with either Concise (3M Espe) or Prisma Shield (Caulk/Dentsply) sealant agents. A hematoxylin-based staining solution was applied on the occlusal surface 7 days, 18 months, 36 months, and 11 years after occlusal sealing to allow checking of the sealant material on the surface. At each analysis time all occlusal surfaces were photographed, and the photographs corresponding to each time period were analyzed with SigmaScan 4.0 Software. The alterations of the sealed area of each sealant were analyzed with the software and recorded. Next, the measurements of the areas were tabulated and analyzed according to each period. Analysis of variance (ANOVA), with parts subdivided into time, and the t test, with a significance level of 5%, were used. RESULTS: The greatest sealed area was maintained by the sealant Concise. However, over the course of 11 years, all sealants began to show the same level of alteration in sealed area. CONCLUSION: The sealing materials showed alteration in sealed area over time, but they were efficient in controlling caries lesion formation on premolar pits and fissures.

Comparative analysis between three methods of bone estimating age in individuals with down syndrome by mode of the hand and wrist ray

The wrist and hand region has been the most commonly used for estimating age and osseous development due to the great number of ossification centers. The aim was to determine which method, Tanner & Whitehouse's (TW3), Greulich & Pyle's (GP) or Eklof & Ringertz's, more closely relates to the chronological age in subjects with Down syndrome with chronological ages between 61 and 180 months, using wrist and hand radiographs. The sample consisted of 85 radiographs, 52 of males and 33 of females. Eklof & Ringertz's method was computerized (Radiomemory). Greulich & Pyle's atlas was used and compared with the wrist and hand radiographs. For the TW3 method, 13 ossification centers were evaluated; for each one of them, there are seven or eight development stages to which scores are assigned; these scores are then added and the results are transformed into osseous age values. No statistically significant differences were observed between the male and female genders for methods TW3 and GP, contrasting with the observed differences for the Eklof & Ringertz method. Correlation (r2) between osseous and chronological ages was 0.8262 for TW3 and 0.7965 for GP, while for the method of Eklof & Ringertz, it was 0.7656 for females and 0.8353 for males. The author concluded that the osseous age assessment method that better related to the chronological age was the TW3, followed by Greulich & Pyle's and Eklof & Ringertz's.

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Geometry-Aware Multiscale Image Registration via OBBTree-Based Polyaffine Log-Demons

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

A navigation system for percutaneous needle interventions based on PET/CT images: design, workflow and error analysis of soft tissue and bone punctures

Percutaneous needle intervention based on PET/CT images is effective, but exposes the patient to unnecessary radiation due to the increased number of CT scans required. Computer assisted intervention can reduce the number of scans, but requires handling, matching and visualization of two different datasets. While one dataset is used for target definition according to metabolism, the other is used for instrument guidance according to anatomical structures. No navigation systems capable of handling such data and performing PET/CT image-based procedures while following clinically approved protocols for oncologic percutaneous interventions are available. The need for such systems is emphasized in scenarios where the target can be located in different types of tissue such as bone and soft tissue. These two tissues require different clinical protocols for puncturing and may therefore give rise to different problems during the navigated intervention. Studies comparing the performance of navigated needle interventions targeting lesions located in these two types of tissue are not often found in the literature. Hence, this paper presents an optical navigation system for percutaneous needle interventions based on PET/CT images. The system provides viewers for guiding the physician to the target with real-time visualization of PET/CT datasets, and is able to handle targets located in both bone and soft tissue. The navigation system and the required clinical workflow were designed taking into consideration clinical protocols and requirements, and the system is thus operable by a single person, even during transition to the sterile phase. Both the system and the workflow were evaluated in an initial set of experiments simulating 41 lesions (23 located in bone tissue and 18 in soft tissue) in swine cadavers. We also measured and decomposed the overall system error into distinct error sources, which allowed for the identification of particularities involved in the process as well as highlighting the differences between bone and soft tissue punctures. An overall average error of 4.23 mm and 3.07 mm for bone and soft tissue punctures, respectively, demonstrated the feasibility of using this system for such interventions. The proposed system workflow was shown to be effective in separating the preparation from the sterile phase, as well as in keeping the system manageable by a single operator. Among the distinct sources of error, the user error based on the system accuracy (defined as the distance from the planned target to the actual needle tip) appeared to be the most significant. Bone punctures showed higher user error, whereas soft tissue punctures showed higher tissue deformation error.