Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Spectral Color Appearance Modeling

Kuvien laatu on tutkituimpia ja käytetyimpiä aiheita. Tässä työssä tarkastellaan värin laatu ja spektrikuvia. Työssä annetaan yleiskuva olemassa olevista pakattujen ja erillisten kuvien laadunarviointimenetelmistä painottaen näiden menetelmien soveltaminen spektrikuviin. Tässä työssä esitellään spektriväriulkomuotomalli värikuvien laadunarvioinnille. Malli sovelletaan spektrikuvista jäljennettyihin värikuviin. Malli pohjautuu sekä tilastolliseen spektrikuvamalliin, joka muodostaa yhteyden spektrikuvien ja valokuvien parametrien välille, että kuvan yleiseen ulkomuotoon. Värikuvien tilastollisten spektriparametrien ja fyysisten parametrien välinen yhteys on varmennettu tietokone-pohjaisella kuvamallinnuksella. Mallin ominaisuuksien pohjalta on kehitetty koekäyttöön tarkoitettu menetelmä värikuvien laadunarvioinnille. On kehitetty asiantuntija-pohjainen kyselymenetelmä ja sumea päättelyjärjestelmä värikuvien laadunarvioinnille. Tutkimus osoittaa, että spektri-väri –yhteys ja sumea päättelyjärjestelmä soveltuvat tehokkaasti värikuvien laadunarviointiin.

Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

Contribution of S opponent cells to color appearance

We measured the regions in isoluminant color space over which observers perceive red, yellow, green, and blue and examined the extent to which the colors vary in perceived amount within these regions. We compared color scaling of various isoluminant stimuli by using large spots, which activate all cone types, to that with tiny spots in the central foveola, where S cones, and thus S opponent (So) cell activity, are largely or entirely absent. The addition of So input to that from the L and M opponent cells changes the chromatic appearance of all colors, affecting each primary color in different chromatic regions in the directions and by the amount predicted by our color model. Shifts from white to the various chromatic stimuli we used produced sinusoidal variations in cone activation as a function of color angle for each cone type and in the responses of lateral geniculate cells. However, psychophysical color-scaling functions for 2° spots were nonsinusoidal, being much more peaked. The color-scaling functions are well fit by sine waves raised to exponents between 1 and 3. The same is true for the color responses of a large subpopulation of striate cortex cells. The narrow color tuning, the discrepancies between the spectral loci of the peaks of the color-scaling curves and those of lateral geniculate cells, and the changes in color appearance produced by eliminating So input provide evidence for a cortical processing stage at which the color axes are rotated by a combination of the outputs of So cells with those of L and M opponent cells in the manner that we postulated earlier. There seems to be an expansive response nonlinearity at this stage.

Värivaikutelmatekijöitä huomioivat värierojen laskentamallit

Värin havaitseminen on monimutkainen tapahtuma, johon vaikuttaa lukuisia tekijöitä. Havaittua väriä eli värivaikutelmaa ennustavat mallit huomioivat taustan ja valonlähteen kromaattisuus- ja intensiteettiominaisuuksia. Värejä käyttävässä teollisuudessa on tarve värien määrittelyn lisäksi mitata värieroja esimerkiksi värillisten tuotteiden laadunvalvonnassa. Värivaikutelmamalleja ja värierojenlaskentamalleja on pitkään kehitetty toisistaan erillisinä. Tässä työssä tarkastellaan värivaikutelmailmiöitä ja sekä värivaikutelma- ja värieromallien ominaisuuksia. Lisäksi selvitetään värivaikutelmamallien ja värieromallien yhteensovittamista.

Modelling and segmentation of the vocal tract during speech production by using deformable models in magnetic resonance images

The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.

A comparison of global estimates of marine primary production from ocean color

The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe

Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models.

Global color estimation of special-effect coatings from measurements by commercially available portable multiangle spectrophotometers

Colors of special-effect coatings have strong dependence on illumination/viewing geometry and an appealing appearance. An open question is to ask about the minimum number of measurement geometries required to completely characterize their observed color shift. A recently published principal components analysis (PCA)-based procedure to estimate the color of special-effect coatings at any geometry from measurements at a reduced set of geometries was tested in this work by using the measurement geometries of commercial portable multiangle spectrophotometers X-Rite MA98, Datacolor FX10, and BYK-mac as reduced sets. The performance of the proposed PCA procedure for the color-shift estimation for these commercial geometries has been examined for 15 special-effect coatings. Our results suggest that for rendering the color appearance of 3D objects covered with special-effect coatings, the color accuracy obtained with this procedure may be sufficient. This is the case especially if geometries of X-Rite MA98 or Datacolor FX10 are used.

Measuring color differences in gonioapparent materials used in the automotive industry

This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.

Avaliação do AAM - Active Appearance Model para detecção de regiões de interesse em radiografias carpais na estimativa da idade óssea através do método TW

In several areas of health professionals (pediatricians, nutritionists, orthopedists, endocrinologists, dentists, etc.) are used in the assessment of bone age to diagnose growth disorders in children. Through interviews with specialists in diagnostic imaging and research done in the literature, we identified the TW method - Tanner and Whitehouse as the most efficient. Even achieving better results than other methods, it is still not the most used, due to the complexity of their use. This work presents the possibility of automation of this method and therefore that its use more widespread. Also in this work, they are met two important steps in the evaluation of bone age, identification and classification of regions of interest. Even in the radiography in which the positioning of the hands were not suitable for TW method, the identification algorithm of the fingers showed good results. As the use AAM - Active Appearance Models showed good results in the identification of regions of interest even in radiographs with high contrast and brightness variation. It has been shown through appearance, good results in the classification of the epiphysis in their stages of development, being chosen the average epiphysis finger III (middle) to show the performance. The final results show an average percentage of 90% hit and misclassified, it was found that the error went away just one stage of the correct stage.

Studies on the characterization of dental whitening process by using both hyperspectral imaging and colorimeter techniques

A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.

A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

Study of clarification process of sugar cane juice for consumption

Sugar cane juice or garapa darkens quickly after extraction due to the oxidation of some of its constituents harming its commercialization thus requiring rapid consumption. The objective of this study was to develop a mild process for sugar cane clarification, obtaining a cloudy, greenish-yellow beverage. The following parameters were combined to aiming at this objective: heat treatment at 65 ºC/50 minutes; pH change (to 7.0, 7.5, and 8.0); addition of flocculant (0, 30, and 60 ppm Aluminum polychloride or APC - "Panclar P-1010"), and clarifier aid (0, 2, or 4 ppm of positively charged polyelectrolyte - "Magnafloc LT-27"). The decantation time was 45 minutes and the supernatant liquid was removed with a vacuum pump. The treatments were defined using the Response Surface Methodology and were submitted to physicochemical analysis for turbidity (%), total polysaccharide content (µg.mL-1), dextran content (µg.mL-1), and sensory analysis (acceptance test) for the attributes of color, appearance, and turbidity. It was concluded that the addition of 60 ppm APC, pH 8, and 0 ppm polyelectrolyte represented the best treatment to obtain a low polysaccharide content, 90% turbidity, and high scores for color, appearance, and turbidity. The beverage was sensorially well accepted by consumers.