Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

Color texture analysis based on fractal descriptors

Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. (C) 2011 Elsevier Ltd. All rights reserved.

A palaeobiologist's guide to 'virtual' micro-CT preparation

This paper provides a brief but comprehensive guide to creating, preparing and dissecting a 'virtual' fossil, using a worked example to demonstrate some standard data processing techniques. Computed tomography (CT) is a 3D imaging modality for producing 'virtual' models of an object on a computer. In the last decade, CT technology has greatly improved, allowing bigger and denser objects to be scanned increasingly rapidly. The technique has now reached a stage where systems can facilitate large-scale, non-destructive comparative studies of extinct fossils and their living relatives. Consequently the main limiting factor in CT-based analyses is no longer scanning, but the hurdles of data processing (see disclaimer). The latter comprises the techniques required to convert a 3D CT volume (stack of digital slices) into a virtual image of the fossil that can be prepared (separated) from the matrix and 'dissected' into its anatomical parts. This technique can be applied to specimens or part of specimens embedded in the rock matrix that until now have been otherwise impossible to visualise. This paper presents a suggested workflow explaining the steps required, using as example a fossil tooth of Sphenacanthus hybodoides (Egerton), a shark from the Late Carboniferous of England. The original NHMUK copyrighted CT slice stack can be downloaded for practice of the described techniques, which include segmentation, rendering, movie animation, stereo-anaglyphy, data storage and dissemination. Fragile, rare specimens and type materials in university and museum collections can therefore be virtually processed for a variety of purposes, including virtual loans, website illustrations, publications and digital collections. Micro-CT and other 3D imaging techniques are increasingly utilized to facilitate data sharing among scientists and on education and outreach projects. Hence there is the potential to usher in a new era of global scientific collaboration and public communication using specimens in museum collections.

Fractal descriptors based on Fourier spectrum applied to texture analysis

This work proposes the development and study of a novel technique lot the generation of fractal descriptors used in texture analysis. The novel descriptors are obtained from a multiscale transform applied to the Fourier technique of fractal dimension calculus. The power spectrum of the Fourier transform of the image is plotted against the frequency in a log-log scale and a multiscale transform is applied to this curve. The obtained values are taken as the fractal descriptors of the image. The validation of the proposal is performed by the use of the descriptors for the classification of a dataset of texture images whose real classes are previously known. The classification precision is compared to other fractal descriptors known in the literature. The results confirm the efficiency of the proposed method. (C) 2012 Elsevier B.V. All rights reserved.

REALISTIC IVUS IMAGE GENERATION IN DIFFERENT INTRALUMINAL PRESSURES

Intravascular ultrasound (IVUS) phantoms are important to calibrate and evaluate many IVUS imaging processing tasks. However, phantom generation is never the primary focus of related works; hence, it cannot be well covered, and is usually based on more than one platform, which may not be accessible to investigators. Therefore, we present a framework for creating representative IVUS phantoms, for different intraluminal pressures, based on the finite element method and Field II. First, a coronary cross-section model is selected. Second, the coronary regions are identified to apply the properties. Third, the corresponding mesh is generated. Fourth, the intraluminal force is applied and the deformation computed. Finally, the speckle noise is incorporated. The framework was tested taking into account IVUS contrast, noise and strains. The outcomes are in line with related studies and expected values. Moreover, the framework toolbox is freely accessible and fully implemented in a single platform. (E-mail: fernando.okara@gmail.com) (c) 2012 World Federation for Ultrasound in Medicine & Biology.

Comparison between multiplanar and rendering modes in the assessment of fetal atrioventricular valve areas by 3D/4D ultrasonography

Objective: To compare the agreement of multiplanar and rendering modes in the assessment fetal atrioventricular valves (mitral and tricuspid) areas by three-dimensional (3D) ultrasonography using the software spatio-temporal image correlation (STIC). Methods: We conducted a prospective cross-sectional study with normal pregnant women, with single fetuses, between 18-33 weeks. To measure the areas, we used the plan of four-chamber view. In the case of multiplanar, the plane was rotated on the axis "Z" form the heart to position at 9h. For rendering, the green line (region of interest - ROI) was placed from the atria of the heart perpendicular to the crux. The agreement was assessed by a Bland-Altman (limits of agreement) using the relative difference between the measures: ((rendering mode) - (multiplanar mode)) / (average). Results: 328 fetuses were evaluated. We have not identified the occurrence of systematic error between methods: the average relative difference was 1.62% (-2.07% to 5.32%, confidence interval 95%) in the mitral and 1.77% (- 1.08% to 4.62%) in the tricuspid valve. The limits of agreement between methods were -65.26% to 68.51% for the mitral and -49.91% to 53.45% for the tricuspid. Conclusions: There was no systematic error between modes and thus the observed values for the area of fetal atrioventricular valves can be used for comparisons needs to be corrected. However, relatively large variations may be observed when repeating the measurement area by different modes.

EDGE-PRESERVING SPECKLE TEXTURE REMOVAL BY INTERFERENCE-BASED SPECKLE FILTERING FOLLOWED BY ANISOTROPIC DIFFUSION

Ultrasonography has an inherent noise pattern, called speckle, which is known to hamper object recognition for both humans and computers. Speckle noise is produced by the mutual interference of a set of scattered wavefronts. Depending on the phase of the wavefronts, the interference may be constructive or destructive, which results in brighter or darker pixels, respectively. We propose a filter that minimizes noise fluctuation while simultaneously preserving local gray level information. It is based on steps to attenuate the destructive and constructive interference present in ultrasound images. This filter, called interference-based speckle filter followed by anisotropic diffusion (ISFAD), was developed to remove speckle texture from B-mode ultrasound images, while preserving the edges and the gray level of the region. The ISFAD performance was compared with 10 other filters. The evaluation was based on their application to images simulated by Field II (developed by Jensen et al.) and the proposed filter presented the greatest structural similarity, 0.95. Functional improvement of the segmentation task was also measured, comparing rates of true positive, false positive and accuracy. Using three different segmentation techniques, ISFAD also presented the best accuracy rate (greater than 90% for structures with well-defined borders). (E-mail: fernando.okara@gmail.com) (C) 2012 World Federation for Ultrasound in Medicine & Biology.

Texture descriptor based on partially self-avoiding deterministic walker on networks

Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.

Classification of polymers insulators hydrophobicity basead on digital image processing

Although the hydrophobicity is usually an arduous parameter to be determined in the field, it has been pointed out as a good option to monitor aging of polymeric outdoor insulators. Concerning this purpose, digital image processing of photos taken from wet insulators has been the main technique nowadays. However, important challenges on this technique still remain to be overcome, such as; images from non-controlled illumination conditions can interfere on analyses and no existence of standard surfaces with different levels of hydrophobicity. In this paper, the photo image samples were digitally filtered to reduce the illumination influence, and hydrophobic surface samples were prepared from wetting silicon surfaces with solution of water-alcohol. Furthermore norevious studies triying to quantify and relate these properties in a mathematical function were found, that could be used in the field by the electrical companies. Based on such considerations, high quality images of countless hydrophobic surfaces were obtained and three different image processing methodologies, the fractal dimension and two Haralick textures descriptors, entropy and homogeneity, associated with several digital filters, were compared. The entropy parameter Haralick's descriptors filtered with the White Top-Hat filter presented the best result to classify the hydrophobicity.

Chitosan-based biomaterials used in critical-size bone defects: radiographic study in rat's calvaria

OBJETIVO: Este estudo avaliou através de imagens radiográficas digitais, a ação de biomateriais de quitosana e de cloridrato de quitosana, com baixo e alto peso molecular, utilizados na correção de defeitos ósseos de tamanho crítico (DOTC)em calvária de ratos. MATERIAL E MÉTODO: DOTCs com 8 mm de diâmetro foram criados cirurgicamente na calvária de 50 ratos Holtzman. Em 10 animais o defeito foi preenchido foram preenchidos com coágulo sanguíneo (controle negativo). Os 40 animais restantes foram divididos de acordo com o biomaterial utilizado no preenchimento do defeito (quitosana de baixo peso e de alto peso molecular, e cloridrato de quitosana de baixo e de alto peso molecular), e foram avaliados em dois períodos experimentais (15 e 60 dias), totalizando 5 animais/biomaterial/período de avaliação. RESULTADO: A avaliação radiográfica foi feita utilizando duas radiografias digitais do crânio do animal: uma tomada logo após o defeito ósseo ser criado e a outra no momento do sacrifício. Nessas imagens, foi avaliada a densidade óssea radiográfica inicial e a final na área do defeito, que foram comparadas. As análises na densidade óssea radiográfica indicaram aumento da densidade óssea radiográfica dos DOTCs tratados para todos os biomateriais testados, em ambos os períodos. Resultados semelhantes foram encontrados no grupo controle. CONCLUSÃO: Conclui-se que os biomateriais de quitosana testados não foram capazes de aumentar a densidade radiográfica em DOTC realizados em calvária de ratos.

Quantitative analysis of photodynamic therapy effects in rat mammary tumor vascular density using image-pro plus software

Photodynamic therapy (PDT) is a treatment modality that has advanced rapidly in recent years. It causes tissue and vascular damage with the interaction of a photosensitizing agent (PS), light of a proper wavelength, and molecular oxygen. Evaluation of vessel damage usually relies on histopathology evaluation. Results are often qualitative or at best semi-quantitative based on a subjective system. The aim of this study was to evaluate, using CD31 immunohistochem- istry and image analysis software, the vascular damage after PDT in a well-established rodent model of chemically induced mammary tumor. Fourteen Sprague-Dawley rats received a single dose of 7,12-dimethylbenz(a)anthraxcene (80 mg/kg by gavage), treatment efficacy was evaluated by comparing the vascular density of tumors after treatment with Photogem® as a PS, intraperitoneally, followed by interstitial fiber optic lighting, from a diode laser, at 200 mW/cm and light dose of 100 J/cm directed against his tumor (7 animals), with a control group (6 animals, no PDT). The animals were euthanized 30 hours after the lighting and mammary tumors were removed and samples from each lesion were formalin-fixed. Immunostained blood vessels were quantified by Image Pro-Plus version 7.0. The control group had an average of 3368.6 ± 4027.1 pixels per picture and the treated group had an average of 779 ± 1242.6 pixels per area (P < 0.01), indicating that PDT caused a significant decrease in vascular density of mammary tumors. The combined immu- nohistochemistry using CD31, with selection of representative areas by a trained pathology, followed by quantification of staining using Image Pro-Plus version 7.0 system was a practical and robust methodology for vessel damage evalua- tion, which probably could be used to assess other antiangiogenic treatments.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

Supervised classification of basaltic aggregate particles based on texture properties

The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.