Animated solid model of the lung constructed from unsynchronized MR sequential images

This work discusses a 4D lung reconstruction method from unsynchronized MR sequential images. The lung, differently from the heart, does not have its own muscles, turning impossible to see its real movements. The visualization of the lung in motion is an actual topic of research in medicine. CT (Computerized Tomography) can obtain spatio-temporal images of the heart by synchronizing with electrocardiographic waves. The FOV of the heart is small when compared to the lung`s FOV. The lung`s movement is not periodic and is susceptible to variations in the degree of respiration. Compared to CT, MR (Magnetic Resonance) imaging involves longer acquisition times and it is not possible to obtain instantaneous 3D images of the lung. For each slice, only one temporal sequence of 2D images can be obtained. However, methods using MR are preferable because they do not involve radiation. In this paper, based on unsynchronized MR images of the lung an animated B-Repsolid model of the lung is created. The 3D animation represents the lung`s motion associated to one selected sequence of MR images. The proposed method can be divided in two parts. First, the lung`s silhouettes moving in time are extracted by detecting the presence of a respiratory pattern on 2D spatio-temporal MR images. This approach enables us to determine the lung`s silhouette for every frame, even on frames with obscure edges. The sequence of extracted lung`s silhouettes are unsynchronized sagittal and coronal silhouettes. Using our algorithm it is possible to reconstruct a 3D lung starting from a silhouette of any type (coronal or sagittal) selected from any instant in time. A wire-frame model of the lung is created by composing coronal and sagittal planar silhouettes representing cross-sections. The silhouette composition is severely underconstrained. Many wire-frame models can be created from the observed sequences of silhouettes in time. Finally, a B-Rep solid model is created using a meshing algorithm. Using the B-Rep solid model the volume in time for the right and left lungs were calculated. It was possible to recognize several characteristics of the 3D real right and left lungs in the shaded model. (C) 2007 Elsevier Ltd. All rights reserved.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required, The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

Evaluation of proximal caries in images resulting from different modes of radiographic digitalization

Objective: The aim of this study was to evaluate the performances of observers in diagnosing proximal caries in digital images obtained from digital bitewing radiographs using two scanners and four digital cameras in Joint Photographic Experts Group (JPEG) and tagged image file format (TIFF) files, and comparing them with the original conventional radiographs. Method: In total, 56 extracted teeth were radiographed with Kodak Insight film (Eastman Kodak, Rochester, NY) in a Kaycor Yoshida X-ray device (Kaycor X-707;Yoshida Dental Manufacturing Co., Tokyo, Japan) operating at 70 kV and 7 mA with an exposure time of 0.40 s. The radiographs were obtained and scanned by CanonScan D646U (Canon USA Inc., Newport News, VA) and Genius ColorPage HR7X (KYE Systems Corp. America, Doral, FL) scanners, and by Canon Powershot G2 (Canon USA Inc.), Canon RebelXT (Canon USA Inc.), Nikon Coolpix 8700 (Nikon Inc., Melville, NY), and Nikon D70s (Nikon Inc.) digital cameras in JPEG and TIFF formats. Three observers evaluated the images. The teeth were then observed under the microscope in polarized light for the verification of the presence and depth of the carious lesions. Results: The probability of no diagnosis ranged from 1.34% (Insight film) to 52.83% (CanonScan/JPEG). The sensitivity ranged from 0.24 (Canon RebelXT/JPEG) to 0.53 (Insight film), the specificity ranged from 0.93 (Nikon Coolpix/JPEG, Canon Powershot/TIFF, Canon RebelXT/JPEG and TIFF) to 0.97 (CanonScan/TIFF and JPEG) and the accuracy ranged from 0.82 (Canon RebelXT/JPEG) to 0.91 (CanonScan/JPEG). Conclusion: The carious lesion diagnosis did not change in either of the file formats (JPEG and TIFF) in which the images were saved for any of the equipment used. Only the CanonScan scanner did not have adequate performance in radiography digitalization for caries diagnosis and it is not recommended for this purpose. Dentomaxillofacial Radiology (2011) 40, 338-343. doi: 10.1259/dmfr/67185962

Dopant extraction from scanning capacitance microscopy measurements of p-n junctions using combined inverse modeling and forward simulation

This article proposes a more accurate approach to dopant extraction using combined inverse modeling and forward simulation of scanning capacitance microscopy (SCM) measurements on p-n junctions. The approach takes into account the essential physics of minority carrier response to the SCM probe tip in the presence of lateral electric fields due to a p-n junction. The effects of oxide fixed charge and interface state densities in the grown oxide layer on the p-n junction samples were considered in the proposed method. The extracted metallurgical and electrical junctions were compared to the apparent electrical junction obtained from SCM measurements. (C) 2002 American Institute of Physics.

Unsaturated diffusivity functions for concrete derived from NMR images

Deterioration of concrete or reinforcing steel through excessive contaminant concentration is often the result of repeated wetting and drying cycles. At each cycle, the absorption of water carries new contaminants into the unsaturated concrete. Nuclear Magnetic Resonance (NMR) is used with large concrete samples to observe the shape of the wetting profile during a simple one-dimensional wetting process. The absorption of water by dry concrete is modelled by a nonlinear diffusion equation with the unsaturated hydraulic diffusivity being a strongly nonlinear function of the moisture content. Exponential and power functions are used for the hydraulic diffusivity and corresponding solutions of the diffusion equation adequately predict the shape of the experimental wetting profile. The shape parameters, describing the wetting profile, vary little between different blends and are relatively insensitive to subsequent re-wetting experiments allowing universal parameters to be suggested for these concretes.

Automated image analysis of lung branching morphogenesis from microscopic images of fetal rat explants

Background: Regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. This work presents a new methodology to accurately quantify the epithelial, outer contour and peripheral airway buds of lung explants during cellular development from microscopic images. Methods: The outer contour was defined using an adaptive and multi-scale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelial was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds were counted as the skeleton branched ends from a skeletonized image of the lung inner epithelial. Results: The time for lung branching morphometric analysis was reduced in 98% in contrast to the manual method. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Non-significant differences were found between the automatic and manual results in all culture days. Conclusions: The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lightning characteristics and allowing a reliable comparison between different researchers.

Evaluation of the respiratory motion effect in small animal PET images with GATE Monte Carlo simulations

The rapid growth in genetics and molecular biology combined with the development of techniques for genetically engineering small animals has led to increased interest in in vivo small animal imaging. Small animal imaging has been applied frequently to the imaging of small animals (mice and rats), which are ubiquitous in modeling human diseases and testing treatments. The use of PET in small animals allows the use of subjects as their own control, reducing the interanimal variability. This allows performing longitudinal studies on the same animal and improves the accuracy of biological models. However, small animal PET still suffers from several limitations. The amounts of radiotracers needed, limited scanner sensitivity, image resolution and image quantification issues, all could clearly benefit from additional research. Because nuclear medicine imaging deals with radioactive decay, the emission of radiation energy through photons and particles alongside with the detection of these quanta and particles in different materials make Monte Carlo method an important simulation tool in both nuclear medicine research and clinical practice. In order to optimize the quantitative use of PET in clinical practice, data- and image-processing methods are also a field of intense interest and development. The evaluation of such methods often relies on the use of simulated data and images since these offer control of the ground truth. Monte Carlo simulations are widely used for PET simulation since they take into account all the random processes involved in PET imaging, from the emission of the positron to the detection of the photons by the detectors. Simulation techniques have become an importance and indispensable complement to a wide range of problems that could not be addressed by experimental or analytical approaches.

Towards an efficient and robust foot classification from pedobarographic images

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Modeling Allee Effect from Beta(p, 2) Densities

In this work we develop and investigate generalized populational growth models, adjusted from Beta(p, 2) densities, with Allee effect. The use of a positive parameter leads the presented generalization, which yields some more flexible models with variable extinction rates. An Allee limit is incorporated so that the models under study have strong Allee effect.

Three-dimensional modeling of tongue during speech using MRI data

The tongue is the most important and dynamic articulator for speech formation, because of its anatomic aspects (particularly, the large volume of this muscular organ comparatively to the surrounding organs of the vocal tract) and also due to the wide range of movements and flexibility that are involved. In speech communication research, a variety of techniques have been used for measuring the three-dimensional vocal tract shapes. More recently, magnetic resonance imaging (MRI) becomes common; mainly, because this technique allows the collection of a set of static and dynamic images that can represent the entire vocal tract along any orientation. Over the years, different anatomical organs of the vocal tract have been modelled; namely, 2D and 3D tongue models, using parametric or statistical modelling procedures. Our aims are to present and describe some 3D reconstructed models from MRI data, for one subject uttering sustained articulations of some typical Portuguese sounds. Thus, we present a 3D database of the tongue obtained by stack combinations with the subject articulating Portuguese vowels. This 3D knowledge of the speech organs could be very important; especially, for clinical purposes (for example, for the assessment of articulatory impairments followed by tongue surgery in speech rehabilitation), and also for a better understanding of acoustic theory in speech formation.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

Multimedia fate modeling and comparative impact on freshwater ecosystems of pharmaceuticals from biosolids-amended soils

This study modeled the impact on freshwater ecosystems of pharmaceuticals detected in biosolids following application on agricultural soils. The detected sulfonamides and hydrochlorothiazide displayed comparatively moderate retention in solid matrices and, therefore, higher transfer fractions from biosolids to the freshwater compartment. However, the residence times of these pharmaceuticals in freshwater were estimated to be short due to abiotic degradation processes. The non-steroidal anti-inflammatory mefenamic acid had the highest environmental impact on aquatic ecosystems and warrants further investigation. The estimation of the solid-water partitioning coefficient was generally the most influential parameter of the probabilistic comparative impact assessment. These results and the modeling approach used in this study serve to prioritize pharmaceuticals in the research effort to assess the risks and the environmental impacts on aquatic biota of these emerging pollutants.

Fatty liver automatic diagnosis from ultrasound images

In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis, also known as, fatty liver, from ultrasound images. The features, automatically extracted from the ultrasound images used by the classifier, are basically the ones used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The main novelty of the method is the utilization of the speckle noise that corrupts the ultrasound images to compute textural features of the liver parenchyma relevant for the diagnosis. The algorithm uses the Bayesian framework to compute a noiseless image, containing anatomic and echogenic information of the liver and a second image containing only the speckle noise used to compute the textural features. The classification results, with the Bayes classifier using manually classified data as ground truth show that the automatic classifier reaches an accuracy of 95% and a 100% of sensitivity.