Task-based annotation and retrieval for image information management

Continuing advances in digital image capture and storage are resulting in a proliferation of imagery and associated problems of information overload in image domains. In this work we present a framework that supports image management using an interactive approach that captures and reuses task-based contextual information. Our framework models the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. During image analysis, interactions are captured and a task context is dynamically constructed so that human expertise, proficiency and knowledge can be leveraged to support other users in carrying out similar domain tasks using case-based reasoning techniques. In this article we present our framework for capturing task context and describe how we have implemented the framework as two image retrieval applications in the geo-spatial and medical domains. We present an evaluation that tests the efficiency of our algorithms for retrieving image context information and the effectiveness of the framework for carrying out goal-directed image tasks. © 2010 Springer Science+Business Media, LLC.

Content-Based Image Retrieval for Computer Tomography Images Using Wavelet Descriptors

An approach to building a CBIR-system for searching computer tomography images using the methods of wavelet-analysis is presented in this work. The index vectors are constructed on the basis of the local features of the image and on their positions. The purpose of the proposed system is to extract visually similar data from the individual personal records and from analogous analysis of other patients.

Scheduling medical application workloads on virtualized computing systems

This dissertation presents and evaluates a methodology for scheduling medical application workloads in virtualized computing environments. Such environments are being widely adopted by providers of "cloud computing" services. In the context of provisioning resources for medical applications, such environments allow users to deploy applications on distributed computing resources while keeping their data secure. Furthermore, higher level services that further abstract the infrastructure-related issues can be built on top of such infrastructures. For example, a medical imaging service can allow medical professionals to process their data in the cloud, easing them from the burden of having to deploy and manage these resources themselves. In this work, we focus on issues related to scheduling scientific workloads on virtualized environments. We build upon the knowledge base of traditional parallel job scheduling to address the specific case of medical applications while harnessing the benefits afforded by virtualization technology. To this end, we provide the following contributions: (1) An in-depth analysis of the execution characteristics of the target applications when run in virtualized environments. (2) A performance prediction methodology applicable to the target environment. (3) A scheduling algorithm that harnesses application knowledge and virtualization-related benefits to provide strong scheduling performance and quality of service guarantees. In the process of addressing these pertinent issues for our target user base (i.e. medical professionals and researchers), we provide insight that benefits a large community of scientific application users in industry and academia. Our execution time prediction and scheduling methodologies are implemented and evaluated on a real system running popular scientific applications. We find that we are able to predict the execution time of a number of these applications with an average error of 15%. Our scheduling methodology, which is tested with medical image processing workloads, is compared to that of two baseline scheduling solutions and we find that it outperforms them in terms of both the number of jobs processed and resource utilization by 20–30%, without violating any deadlines. We conclude that our solution is a viable approach to supporting the computational needs of medical users, even if the cloud computing paradigm is not widely adopted in its current form.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

Morphological analysis of pitting corrosion in AISI 310S austenitic stainless steel after salt spray exposition

This paper aims to study evolution of increase, distribution and classification of pits in 310S austenitic stainless steels obtained in the state as-received and heat-treated under different exposure times in saline. This work applicability has been based on a technique development for morphologic characterization of localized corrosion associated with description aspects of shapes, size and population-specific parameters. Methodology has been consisted in the following steps: specimens preparation, corrosion tests via salt spray in different conditions, microstructural analysis, pits profiles analysis and images analysis, digital processing and image analysis in order to characterize the pits distribution, morphology and size. Results obtained in digital processing and profiles image analysis have been subjected to statistical analysis using median as parameter in the alloy as received and treated. The alloy as received displays the following morphology: hemispheric pits> transition region A> transition region B> irregular> conic. The pits amount in the treated alloy at each exposure time is: transition region B> hemispherical> transition region A> conic> irregular.

X-ray computed tomography to quantify tree rooting spatial distributions

Poor root development due to constraining soil conditions could be an important factor influencing health of urban trees. Therefore, there is a need for efficient techniques to analyze the spatial distribution of tree roots. An analytical procedure for describing tree rooting patterns from X-ray computed tomography (CT) data is described and illustrated. Large irregularly shaped specimens of undisturbed sandy soil were sampled from Various positions around the base of trees using field impregnation with epoxy resin, to stabilize the cohesionless soil. Cores approximately 200 mm in diameter by 500 mm in height were extracted from these specimens. These large core samples were scanned with a medical X-ray CT device, and contiguous images of soil slices (2 mm thick) were thus produced. X-ray CT images are regarded as regularly-spaced sections through the soil although they are not actual 2D sections but matrices of voxels similar to 0.5 mm x 0.5 mm x 2 mm. The images were used to generate the equivalent of horizontal root contact maps from which three-dimensional objects, assumed to be roots, were reconstructed. The resulting connected objects were used to derive indices of the spatial organization of roots, namely: root length distribution, root length density, root growth angle distribution, root spatial distribution, and branching intensity. The successive steps of the method, from sampling to generation of indices of tree root organization, are illustrated through a case study examining rooting patterns of valuable urban trees. (C) 1999 Elsevier Science B.V. All rights reserved.

Proteomic analysis of normal and malignant prostate tissue to identify novel proteins lost in cancer

BACKGROUND. Alterations of important protein pathways, including loss of prostate secretory granules, and disruption of the prostatic secretory pathway have been identified as early events in malignancy. In this study, proteomics was used to map the differences in protein expression between normal and malignant prostate tissues and to identify and analyze differentially expressed proteins in human prostate tissue with particular regard to the proteins lost in malignancy. METHODS. Small quantities of normal and malignant prostate tissue were taken fresh from 34 radical prostatectomy cases. After histological examination, proteins were solubilized from selected tissues and separated using two-dimensional electrophoresis. Using image analysis, the proteome of normal and malignant tissues were mapped and differentially expressed proteins (present in normal and absent in malignant tissue) were identified and subsequently analyzed using peptide mass finger printing and N-terminal sequencing. Western blotting and immunohistochemistry were performed to examine expression profiles and tissue localization of candidate proteins. RESULTS. Comparison of protein maps of normal and malignant prostate were used to identify 20 proteins which were lost in malignant transformation, including prostate specific antigen (PSA), alpha-l antichymotrypsin (ACT), haptoglobin, and lactoylglutathione lyase. Three of the 20 had not previously been reported in human prostate tissue (Ubiquitin-like NEDD8, calponin, and a follistatin-related protein). Western blotting confirmed differences in the expression profiles of NEDD8 and calponin, and immunohistochemistry demonstrated differences in the cellular localization of these two proteins in normal and malignant prostate glands. CONCLUSIONS. The expression of NEDD8, calponin, and the follistatin-related protein in normal prostate tissues is a novel finding and the role of these important functional proteins in normal prostate and their loss or reduced expression in prostate malignancy warrants further investigations. (C) 2002 Wiley-Liss, Inc.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

Cortical Thickness Reduction of Normal Appearing Cortex in Patients with Polymicrogyria

OBJECTIVE To examine cortical thickness and volumetric changes in the cortex of patients with polymicrogyria, using an automated image analysis algorithm. METHODS Cortical thickness of patients with polymicrogyria was measured using magnetic resonance imaging (MRI) cortical surface-based analysis and compared with age-and sex-matched healthy subjects. We studied 3 patients with disorder of cortical development (DCD), classified as polymicrogyria, and 15 controls. Two experienced neuroradiologists performed a conventional visual assessment of the MRIs. The same data were analyzed using an automated algorithm for tissue segmentation and classification. Group and individual average maps of cortical thickness differences were produced by cortical surface-based statistical analysis. RESULTS Patients with polymicrogyria showed increased thickness of the cortex in the same areas identified as abnormal by radiologists. We also identified a reduction in the volume and thickness of cortex within additional areas of apparently normal cortex relative to controls. CONCLUSIONS Our findings indicate that there may be regions of reduced cortical thickness, which appear normal from radiological analysis, in the cortex of patients with polymicrogyria. This finding suggests that alterations in neuronal migration may have an impact in the cortical formation of the cortical areas that are visually normal. These areas are associated or occur concurrently with polymicrogyria.

Microvascular Lymphatic Density Analysis in Cutaneous Regressive and Nonregressive Superficial Spreading Melanomas Using the Lymphatic Marker D2-40

Background: The prognostic significance of spontaneous regression in melanoma, especially thin lesions, has been a controversial issue for the past 20 years, although recent studies suggest that extensive and late regression may be related to worse prognosis. Many data suggest that lymphangiogenesis predicts metastatic spread in melanoma. Methods: We have quantified lymphatic microvascular density (LMVD) in thin (<= 1.0 mm) superficial spreading melanomas comparing regressive and nonregressive melanomas, regressive and nonregressive areas from the same tumor, and early and late histological stages of regression in the same tumor. In addition, we tried to correlate lymphangiogenesis and tumor growth phase. We conducted histological examinations and immunohistochemical analyses using monoclonal antibody D2-40 with subsequent quantification by image analysis of 37 melanomas, 16 regressive and 21 nonregressive (controls). Results: We found higher LMVD in the late stage of regression compared with nonregressive area (internal control) of regressive melanomas. Conclusions: Our study suggest that the late stage of spontaneous regression in thin melanomas may be related to worse prognosis as it showed higher LMVD, and evidence shows that this is related with increased risk of metastatic spread. But this supposition must be confirmed by a longer follow-up for detection of lymph node metastases.

Quantitative and qualitative comparison of 3.0 T and 1.5 T MR imaging of the liver in patients with diffuse parenchymal liver disease

Purpose: The purpose of our study was to compare signal characteristics and image qualities of MR imaging at 3.0 T and 1.5 T in patients with diffuse parenchymal liver disease. Materials and methods: 25 consecutive patients with diffuse parenchymal liver disease underwent abdominal MR imaging at both 3.0 T and 1.5 T within a 6-month interval. A retrospective study was conducted to obtain quantitative and qualitative data from both 3.0 T and 1.5 T MRI. Quantitative image analysis was performed by measuring the signal-to-noise ratios (SNRs) and the contrast-to-noise ratios (CNRs) by the Students t-test. Qualitative image analysis was assessed by grading each sequence on a 3- and 4-point scale, regarding the presence of artifacts and image quality, respectively. Statistical analysis consisted of the Wilcoxon signed-rank test. Results: the mean SNRs and CNRs of the liver parenchyma and the portal vein were significantly higher at 3.0 T than at 1.5 T on portal and equilibrium phases of volumetric interpolated breath-hold examination (VIBE) images (P < 0.05). The mean SNRs were significantly higher at 3.0 T than at 1.5 T on T1-weighted spoiled gradient echo (SGE) images (P < 0.05). However, there were no significantly differences on T2-weighted short-inversion-time inversion recovery (STIR) images. Overall image qualities of the 1.5 T noncontrast T1- and T2-weighted sequences were significantly better than 3.0 T (P < 0.01). In contrast, overall image quality of the 3.0 T post-gadolinium VIBE sequence was significantly better than 1.5 T (P< 0.01). Conclusions: MR imaging of post-gadolinium VIBE sequence at 3.0 T has quantitative and qualitative advantages of evaluating for diffuse parenchymal liver disease. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Shape alterations in the striatum in chorea-acanthocytosis

Chorea-acanthocytosis (ChAc) is an uncommon autosomal recessive disorder due to mutations of the VPS13A gene, which encodes for the membrane protein chorein. ChAc presents with progressive limb and orobuccal chorea, but there is often a marked dysexecutive syndrome. ChAc may first present with neuropsychiatric disturbance such as obsessive-compulsive disorder (OCD), suggesting a particular role for disruption to striatal structures involved in non-motor frontostriatal loops, such as the head of the caudate nucleus. Two previous studies have suggested a marked reduction in volume in the caudate nucleus and putamen, but did not examine morphometric change. We investigated morphometric change in 13 patients with genetically or biochemically confirmed ChAc and 26 age- and gender-matched controls. Subjects underwent magnetic resonance imaging and manual segmentation of the caudate nucleus and putamen, and shape analysis using a non-parametric spherical harmonic technique. Both structures showed significant and marked reductions in volume compared with controls, with reduction greatest in the caudate nucleus. Both structures showed significant shape differences, particularly in the head of the caudate nucleus. No significant correlation was shown between duration of illness and striatal volume or shape, suggesting that much structural change may have already taken place at the time of symptom onset. Our results suggest that striatal neuron loss may occur early in the disease process, and follows a dorsal-ventral gradient that may correlate with early neuropsychiatric and cognitive presentations of the disease. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Analysis of enamel microbiopsies in shed primary teeth by Scanning Electron Microscopy (SEM) and Polarizing Microscopy (PM)

The aims of this study were 1) to verify how close to the theoretically presumed areas are the areas of enamel microbiopsies carried out in vivo or in exfoliated teeth; 2) to test whether the etching solution penetrates beyond the tape borders: 3) to test whether the etching solution demineralizes the enamel in depth. 24 shed upper primary central incisors were randomly divided into two groups: the Rehydrated Teeth Group and the Dry Teeth Group. An enamel microbiopsy was performed, and the enamel microbiopsies were then analyzed by Scanning Electron Microscopy (SEMI) and Polarizing Microscopy (PM). Quantitative birefringence measurements were performed. The ""true"" etched area was determined by measuring the etched enamel using the NIH Image analysis program. Enamel birefringence was compared using the paired t test. There was a statistically significant difference when the etched areas in the Rehydrated teeth were compared with those of the Dry teeth (p = 0.04). The etched areas varied from -11.6% to 73.5% of the presumed area in the Rehydrated teeth, and from 6.6% to 61.3% in the Dry teeth. The mean percentage of variation in each group could be used as a correction factor for the etched area. Analysis of PM pictures shows no evidence of in-depth enamel demineralization by the etching solution. No statistically significant differences in enamel birefringence were observed between values underneath and outside the microbiopsy area in the same tooth, showing that no mineral loss occurred below the enamel superficial layer. Our data showed no evidence of in-depth enamel demineralization by the etching solution used in the enamel microbiopsy proposed for primary enamel. This study also showed a variation in the measured diameter of the enamel microbiopsy in nineteen teeth out of twenty four, indicating that in most cases the etching solution penetrated beyond the tape borders. (C) 2009 Elsevier B.V. All rights reserved.

A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.

On-line analysis of froth surface in coal and mineral flotation using JKFrothCam

The personal computer revolution has resulted in the widespread availability of low-cost image analysis hardware. At the same time, new graphic file formats have made it possible to handle and display images at resolutions beyond the capability of the human eye. Consequently, there has been a significant research effort in recent years aimed at making use of these hardware and software technologies for flotation plant monitoring. Computer-based vision technology is now moving out of the research laboratory and into the plant to become a useful means of monitoring and controlling flotation performance at the cell level. This paper discusses the metallurgical parameters that influence surface froth appearance and examines the progress that has been made in image analysis of flotation froths. The texture spectrum and pixel tracing techniques developed at the Julius Kruttschnitt Mineral Research Centre are described in detail. The commercial implementation, JKFrothCam, is one of a number of froth image analysis systems now reaching maturity. In plants where it is installed, JKFrothCam has shown a number of performance benefits. Flotation runs more consistently, meeting product specifications while maintaining high recoveries. The system has also shown secondary benefits in that reagent costs have been significantly reduced as a result of improved flotation control. (C) 2002 Elsevier Science B.V. All rights reserved.