951 resultados para Automatic image analysis
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Stereology and other image analysis methods have enabled rapid and objective quantitative measurements to be made on histological sections. These mesurements may include total volumes, surfaces, lengths and numbers of cells and blood vessels or pathological lesions. Histological features, however, may not be randomly distributed across a section but exhibit 'dispersion', a departure from randomness either towards regularity or aggregation. Information of population dispersion may be valuable not only in understanding the two-or three-dimensional structure but also in elucidating the pathogenesis of lesions in pathological conditions. This article reviews some of the statistical methods available for studying dispersion. These range from simple tests of whether the distribution of a histological faeture departs significantly from random to more complex methods which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters.
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Objective: To study the density and cross-sectional area of axons in the optic nerve in elderly control subjects and in cases of Alzheimer's disease (AD) using an image analysis system. Methods: Sections of optic nerves from control and AD patients were stained with toluidine blue to reveal axon profiles. Results: The density of axons was reduced in both the center and peripheral portions of the optic nerve in AD compared with control patients. Analysis of axons with different cross-sectional areas suggested a specific loss of the smaller sized axons in AD, i.e., those with areas less that 1.99 μm2. An analysis of axons >11 μm2 in cross-sectional area suggested no specific loss of the larger axons in this group of patients. Conclusions: The data suggest that image analysis provides an accurate and reproducible method of quantifying axons in the optic nerve. In addition, the data suggest that axons are lost throughout the optic nerve with a specific loss of the smaller-sized axons. Loss of the smaller axons may explain the deficits in color vision observed in a significant proportion of patients with AD.
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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.
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We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised by the concentrations of the five main absorbers found in the fundus: retinal haemoglobins, choroidal haemoglobins, choroidal melanin, RPE melanin and macular pigment. These parameters are shown to give rise to distinct variations in the tissue colouration. We use the results of the Monte Carlo simulations to construct an inverse model which maps tissue colouration onto the model parameters. This allows the concentration and distribution of the five main absorbers to be determined from suitable multi-spectral images. We propose the use of "image quotients" to allow this information to be extracted from uncalibrated image data. The filters used to acquire the images are selected to ensure a one-to-one mapping between model parameters and image quotients. To recover five model parameters uniquely, images must be acquired in six distinct spectral bands. Theoretical investigations suggest that retinal haemoglobins and macular pigment can be recovered with RMS errors of less than 10%. We present parametric maps showing the variation of these parameters across the posterior pole of the fundus. The results are in agreement with known tissue histology for normal healthy subjects. We also present an early result which suggests that, with further development, the technique could be used to successfully detect retinal haemorrhages.
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Purpose: To compare graticule and image capture assessment of the lower tear film meniscus height (TMH). Methods: Lower tear film meniscus height measures were taken in the right eyes of 55 healthy subjects at two study visits separated by 6 months. Two images of the TMH were captured in each subject with a digital camera attached to a slit-lamp biomicroscope and stored in a computer for future analysis. Using the best of two images, the TMH was quantified by manually drawing a line across the tear meniscus profile, following which the TMH was measured in pixels and converted into millimetres, where one pixel corresponded to 0.0018 mm. Additionally, graticule measures were carried out by direct observation using a calibrated graticule inserted into the same slit-lamp eyepiece. The graticule was calibrated so that actual readings, in 0.03 mm increments, could be made with a 40× ocular. Results: Smaller values of TMH were found in this study compared to previous studies. TMH, as measured with the image capture technique (0.13 ± 0.04 mm), was significantly greater (by approximately 0.01 ± 0.05 mm, p = 0.03) than that measured with the graticule technique (0.12 ± 0.05 mm). No bias was found across the range sampled. Repeatability of the TMH measurements taken at two study visits showed that graticule measures were significantly different (0.02 ± 0.05 mm, p = 0.01) and highly correlated (r = 0.52, p < 0.0001), whereas image capture measures were similar (0.01 ± 0.03 mm, p = 0.16), and also highly correlated (r = 0.56, p < 0.0001). Conclusions: Although graticule and image analysis techniques showed similar mean values for TMH, the image capture technique was more repeatable than the graticule technique and this can be attributed to the higher measurement resolution of the image capture (i.e. 0.0018 mm) compared to the graticule technique (i.e. 0.03 mm). © 2006 British Contact Lens Association.
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Aim: To determine the theoretical and clinical minimum image pixel resolution and maximum compression appropriate for anterior eye image storage. Methods: Clinical images of the bulbar conjunctiva, palpebral conjunctiva, and corneal staining were taken at the maximum resolution of Nikon:CoolPix990 (2048 × 1360 pixels), DVC:1312C (1280 × 811), and JAI:CV-S3200 (767 × 569) single chip cameras and the JVC:KYF58 (767 × 569) three chip camera. The images were stored in TIFF format and further copies created with reduced resolution or compressed. The images were then ranked for clarity on a 15 inch monitor (resolution 1280 × 1024) by 20 optometrists and analysed by objective image analysis grading. Theoretical calculation of the resolution necessary to detect the smallest objects of clinical interest was also conducted. Results: Theoretical calculation suggested that the minimum resolution should be ≥579 horizontal pixels at 25 × magnification. Image quality was perceived subjectively as being reduced when the pixel resolution was lower than 767 × 569 (p<0.005) or the image was compressed as a BMP or <50% quality JPEG (p<0.005). Objective image analysis techniques were less susceptible to changes in image quality, particularly when using colour extraction techniques. Conclusion: It is appropriate to store anterior eye images at between 1280 × 811 and 767 × 569 pixel resolution and at up to 1:70 JPEG compression.
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Purpose - To generate a reflectance model of the fundus that allows an accurate non-invasive quantification of blood and pigments. Methods - A Monte Carlo simulation was used to produce a mathematical model of light interaction with the fundus at different wavelengths. The model predictions were compared with fundus images from normal volunteers in several spectral bands (peaks at 507, 525, 552, 585, 596 and 611nm). Th e model was then used to calculate the concentration and distribution of the known absorbing components of the fundus. Results - The shape of the statistical distribution of the image data generally corresponded to that of the model data; the model however appears to overestimate the reflectance of the fundus in the longer wavelength region.As the absorption by xanthophyll has no significant eff ect on light transport above 534nm, its distribution in the fundus was quantified: the wavelengths where both shape and distribution of image and model data matched (<553nm) were used to train a neural network which was then applied to every point in the image data. The xanthophyll distribution thus found was in agreement with published literature data in normal subjects. Conclusion - We have developed a method for optimising multi-spectral imaging of the fundus and a computer image analysis capable of estimating information about the structure and properties of the fundus. Th e technique successfully calculates the distribution of xanthophyll in the fundus of healthy volunteers. Further improvement of the model is required to allow the deduction of other parameters from images; investigations in known pathology models are also necessary to establish if this method is of clinical use in detecting early chroido-retinopathies, hence providing a useful screening and diagnostic tool.
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Purpose: To assess the validity and repeatability of objective compared to subjective contact lens fit analysis. Methods: Thirty-five subjects (aged 22.0. ±. 3.0 years) wore two different soft contact lens designs. Four lens fit variables: centration, horizontal lag, post-blink movement in up-gaze and push-up recovery speed were assessed subjectively (four observers) and objectively from slit-lamp biomicroscopy captured images and video. The analysis was repeated a week later. Results: The average of the four experienced observers was compared to objective measures, but centration, movement on blink, lag and push-up recovery speed all varied significantly between them (p <. 0.001). Horizontal lens centration was on average close to central as assessed both objectively and subjectively (p > 0.05). The 95% confidence interval of subjective repeatability was better than objective assessment (±0.128. mm versus ±0.168. mm, p = 0.417), but utilised only 78% of the objective range. Vertical centration assessed objectively showed a slight inferior decentration (0.371. ±. 0.381. mm) with good inter- and intrasession repeatability (p > 0.05). Movement-on-blink was lower estimated subjectively than measured objectively (0.269. ±. 0.179. mm versus 0.352. ±. 0.355. mm; p = 0.035), but had better repeatability (±0.124. mm versus ±0.314. mm 95% confidence interval) unless correcting for the smaller range (47%). Horizontal lag was lower estimated subjectively (0.562. ±. 0.259. mm) than measured objectively (0.708. ±. 0.374. mm, p <. 0.001), had poorer repeatability (±0.132. mm versus ±0.089. mm 95% confidence interval) and had a smaller range (63%). Subjective categorisation of push-up speed of recovery showed reasonable differentiation relative to objective measurement (p <. 0.001). Conclusions: The objective image analysis allows an accurate, reliable and repeatable assessment of soft contact lens fit characteristics, being a useful tool for research and optimisation of lens fit in clinical practice.
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A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. The combination of methods was a compromise between the higher accuracy of point intercept transects and the larger sample area achievable through spot check surveys (Roelfsema and Phinn, 2008, doi:10.1117/12.804806). Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.
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[ES]This paper describes an analysis performed for facial description in static images and video streams. The still image context is first analyzed in order to decide the optimal classifier configuration for each problem: gender recognition, race classification, and glasses and moustache presence. These results are later applied to significant samples which are automatically extracted in real-time from video streams achieving promising results in the facial description of 70 individuals by means of gender, race and the presence of glasses and moustache.
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With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).
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Quantitative imaging in oncology aims at developing imaging biomarkers for diagnosis and prediction of cancer aggressiveness and therapy response before any morphological change become visible. This Thesis exploits Computed Tomography perfusion (CTp) and multiparametric Magnetic Resonance Imaging (mpMRI) for investigating diverse cancer features on different organs. I developed a voxel-based image analysis methodology in CTp and extended its use to mpMRI, for performing precise and accurate analyses at single-voxel level. This is expected to improve reproducibility of measurements and cancer mechanisms’ comprehension and clinical interpretability. CTp has not entered the clinical routine yet, although its usefulness in the monitoring of cancer angiogenesis, due to different perfusion computing methods yielding unreproducible results. Instead, machine learning applications in mpMRI, useful to detect imaging features representative of cancer heterogeneity, are mostly limited to clinical research, because of results’ variability and difficult interpretability, which make clinicians not confident in clinical applications. In hepatic CTp, I investigated whether, and under what conditions, two widely adopted perfusion methods, Maximum Slope (MS) and Deconvolution (DV), could yield reproducible parameters. To this end, I developed signal processing methods to model the first pass kinetics and remove any numerical cause hampering the reproducibility. In mpMRI, I proposed a new approach to extract local first-order features, aiming at preserving spatial reference and making their interpretation easier. In CTp, I found out the cause of MS and DV non-reproducibility: MS and DV represent two different states of the system. Transport delays invalidate MS assumptions and, by correcting MS formulation, I have obtained the voxel-based equivalence of the two methods. In mpMRI, the developed predictive models allowed (i) detecting rectal cancers responding to neoadjuvant chemoradiation showing, at pre-therapy, sparse coarse subregions with altered density, and (ii) predicting clinically significant prostate cancers stemming from the disproportion between high- and low- diffusivity gland components.
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In the agri-food sector, measurement and monitoring activities contribute to high quality end products. In particular, considering food of plant origin, several product quality attributes can be monitored. Among the non-destructive measurement techniques, a large variety of optical techniques are available, including hyperspectral imaging (HSI) in the visible/near-infrared (Vis/NIR) range, which, due to the capacity to integrate image analysis and spectroscopy, proved particularly useful in agronomy and food science. Many published studies regarding HSI systems were carried out under controlled laboratory conditions. In contrast, few studies describe the application of HSI technology directly in the field, in particular for high-resolution proximal measurements carried out on the ground. Based on this background, the activities of the present PhD project were aimed at exploring and deepening knowledge in the application of optical techniques for the estimation of quality attributes of agri-food plant products. First, research activities on laboratory trials carried out on apricots and kiwis for the estimation of soluble solids content (SSC) and flesh firmness (FF) through HSI were reported; subsequently, FF was estimated on kiwis using a NIR-sensitive device; finally, the procyanidin content of red wine was estimated through a device based on the pulsed spectral sensitive photometry technique. In the second part, trials were carried out directly in the field to assess the degree of ripeness of red wine grapes by estimating SSC through HSI, and finally a method for the automatic selection of regions of interest in hyperspectral images of the vineyard was developed. The activities described above have revealed the potential of the optical techniques for sorting-line application; moreover, the application of the HSI technique directly in the field has proved particularly interesting, suggesting further investigations to solve a variety of problems arising from the many environmental variables that may affect the results of the analyses.
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This report describes the realization of a system, in which an object detection model will be implemented, whose aim is to detect the presence of people in images. This system could be used for several applications: for example, it could be carried on board an aircraft or a drone. In this case, the system is designed in such a way that it can be mounted on light/medium weight helicopters, helping the operator to find people in emergency situations. In the first chapter the use of helicopters for civil protection is analysed and applications similar to this case study are listed. The second chapter describes the choice of the hardware devices that have been used to implement a prototype of a system to collect, analyse and display images. At first, the PC necessary to process the images was chosen, based on the characteristics of the algorithms that are necessary to run the analysis. In the further, a camera that could be compatible with the PC was selected. Finally, the battery pack was chosen taking into account the electrical consumption of the devices. The third chapter illustrates the algorithms used for image analysis. In the fourth, some of the requirements listed in the regulations that must be taken into account for carrying on board all the devices have been briefly analysed. In the fifth chapter the activity of design and modelling, with the CAD Solidworks, the devices and a prototype of a case that will house them is described. The sixth chapter discusses the additive manufacturing, since the case was printed exploiting this technology. In the seventh chapter, part of the tests that must be carried out on the equipment to certificate it have been analysed, and some simulations have been carried out. In the eighth chapter the results obtained once loaded the object detection model on a hardware for image analyses were showed. In the ninth chapter, conclusions and future applications were discussed.
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Valproic acid (VPA) and trichostatin A (TSA) are known histone deacetylase inhibitors (HDACIs) with epigenetic activity that affect chromatin supra-organization, nuclear architecture, and cellular proliferation, particularly in tumor cells. In this study, chromatin remodeling with effects extending to heterochromatic areas was investigated by image analysis in non-transformed NIH 3T3 cells treated for different periods with different doses of VPA and TSA under conditions that indicated no loss of cell viability. Image analysis revealed chromatin decondensation that affected not only euchromatin but also heterochromatin, concomitant with a decreased activity of histone deacetylases and a general increase in histone H3 acetylation. Heterochromatin protein 1-α (HP1-α), identified immunocytochemically, was depleted from the pericentromeric heterochromatin following exposure to both HDACIs. Drastic changes affecting cell proliferation and micronucleation but not alteration in CCND2 expression and in ratios of Bcl-2/Bax expression and cell death occurred following a 48-h exposure of the NIH 3T3 cells particularly in response to higher doses of VPA. Our results demonstrated that even low doses of VPA (0.05 mM) and TSA (10 ng/ml) treatments for 1 h can affect chromatin structure, including that of the heterochromatin areas, in non-transformed cells. HP1-α depletion, probably related to histone demethylation at H3K9me3, in addition to the effect of VPA and TSA on histone H3 acetylation, is induced on NIH 3T3 cells. Despite these facts, alterations in cell proliferation and micronucleation, possibly depending on mitotic spindle defects, require a longer exposure to higher doses of VPA and TSA.