Detecting the stages of hyperplasia formation in the breast ducts using ultrasound B-scan images

Presented at the 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, DOI: http://dx.doi.org/10.1109/ISBI.2006.1625064A stochastic decomposition algorithm of the RF Echo into its coherent and diffuse components is used towards estimating the structural parameters of the hyperplastic stages of the breast tissue leading to early breast cancer detection. The discrimination power of the various parameters is studied under a host of conditions such as varying resolution and SNR values using a point scatterer model simulator that mimics epithelium hyperplastic growth in the breast ducts. It is shown that three parameters, in particular, the number of coherent scatterers, the Rayleigh scattering degree and the energy of the diffuse scatterers, prove to show very high ability to discriminate between various stages of hyperplasia even in cases of low resolution and SNR values. Values of Az>0.942 were obtained for resolution less than or equal to 0.4mm even in low SNR values, then it drops below the 0.9 range as the resolution exceeds the 0.4mm range

Tissue characterization and detection of dysplasia using scattered light

Paper presented at the 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA.In this paper, the structural parameters of dysplasia formation in the epithelial tissue are estimated using a stochastic decomposition algorithm (SDM) by means of scattered light. We extract texture parameters obtained from the decomposition that capture the signature of dysplasia formation. These parameters include the number and mean energy of coherent scatterers; deviation from Rayleigh scattering; average energy of diffuse scatterers; and normalized correlation coefficient. The tests are performed on simulations, and tissue-mimicking phantom data. The simulations are based on the light scattered from the cells with varying parameters such as, index of refraction, number of cells, and size of cells. The obtained results demonstrate the proof-of-concept in being able to differentiate between tissue structures that give rise to changes in cell morphology as well as other physical properties such as change in index of refraction. Fusing all the estimated parameter set together results in the differentiation performance (Az value) up to 1(perfect detection) for simulated data, and Az>0.927 for the phantom data

Does chess need intelligence? – A study with young chess players

Although it is widely acknowledged that chess is the best example of an intellectual activity among games, evidence showing the association between any kind of intellectual ability and chess skill has been remarkably sparse. One of the reasons is that most of the studies investigated only one factor (e.g., intelligence), neglecting other factors relevant for the acquisition of chess skill (e.g., amount of practice, years of experience). The present study investigated the chess skill of 57 young chess players using measures of intelligence (WISC III), practice, and experience. Although practice had the most influence on chess skill, intelligence explained some variance even after the inclusion of practice. When an elite subsample of 23 children was tested, it turned out that intelligence was not a significant factor in chess skill, and that, if anything, it tended to correlate negatively with chess skill. This unexpected result is explained by a negative correlation between intelligence and practice in the elite subsample. The study demonstrates the dangers of focusing on a single factor in complex real-world situations where a number of closely interconnected factors operate

The Neural Correlates of Theory of Mindand their Role during Empathy and theGame of Chess: A functional MagneticResonance Imaging Study

Chess involves the capacity to reason iteratively about potential intentional choices of an opponent and therefore involves high levels of explicit theory of mind [ToM] (i.e. ability to infer mental states of others) alongside clear, strategic rule-based decision-making. Functional magnetic resonance imaging was used on 12 healthy male novice chess players to identify cortical regions associated with chess, ToM and empathizing. The blood-oxygenation-level-dependent (BOLD) response for chess and empathizing tasks was extracted from each ToM region. Results showed neural overlap between ToM, chess and empathizing tasks in right-hemisphere temporo-parietal junction (TPJ) [BA40], left-hemisphere superior temporal gyrus [BA22] and posterior cingulate gyrus [BA23/31]. TPJ is suggested to underlie the capacity to reason iteratively about another's internal state in a range of tasks. Areas activated by ToM and empathy included right-hemisphere orbitofrontal cortex and bilateral middle temporal gyrus: areas that become active when there is need to inhibit one's own experience when considering the internal state of another and for visual evaluation of action rationality. Results support previous findings, that ToM recruits a neural network with each region sub-serving a supporting role depending on the nature of the task itself. In contrast, a network of cortical regions primarily located within right- and left-hemisphere medial-frontal and parietal cortex, outside the internal representational network, was selectively recruited during the chess task. We hypothesize that in our cohort of novice chess players the strategy was to employ an iterative thinking pattern which in part involved mentalizing processes and recruited core ToM-related regions

A História da Alimentação: balizas historiográficas

Os M. pretenderam traçar um quadro da História da Alimentação, não como um novo ramo epistemológico da disciplina, mas como um campo em desenvolvimento de práticas e atividades especializadas, incluindo pesquisa, formação, publicações, associações, encontros acadêmicos, etc. Um breve relato das condições em que tal campo se assentou faz-se preceder de um panorama dos estudos de alimentação e temas correia tos, em geral, segundo cinco abardagens Ia biológica, a econômica, a social, a cultural e a filosófica!, assim como da identificação das contribuições mais relevantes da Antropologia, Arqueologia, Sociologia e Geografia. A fim de comentar a multiforme e volumosa bibliografia histórica, foi ela organizada segundo critérios morfológicos. A seguir, alguns tópicos importantes mereceram tratamento à parte: a fome, o alimento e o domínio religioso, as descobertas européias e a difusão mundial de alimentos, gosto e gastronomia. O artigo se encerra com um rápido balanço crítico da historiografia brasileira sobre o tema

Les défis du pluralisme en éducation : essais sur la formation interculturelle /

Bibliogr.: p. 163-17

Stochastic decomposition method for detection of epithelium dysplasia and inflammation using white light spectroscopy imaging

Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, pp. 1956-1959.In this paper, we present a stochastic decomposition method (SDM) that allows the detection of dysplasia in epithelial tissue using white-light spectroscopy imaging. The main goal is to extract the data from the decomposition which will lead to the construction of a feature parameter space corresponding to changes in the tissue morphology related to formation of dysplasia and inflammation. These parameters include the number and mean energy of coherent scatterers; deviation from Rayleigh scattering; residual error variance of the diffuse component; and normalized correlation coefficient. The tests are performed on tissue-mimicking phantom data and tissue data collected from mouse colon in vitro. The obtained results demonstrate effectiveness of the method in differentiating between tissue structures with different cell morphologies. The results are shown by fusing all the estimated parameter set together and also using each parameter separately. Combination of all the features results in an Az value higher than 0.927 for the phantom data. For the tissue data, the best performances for differentiation between pairs of various levels of inflammation are 0.859, 0.983, and 0.999

Fingerprint Alignment Based on Local Feature Combined with Affine Geometric Invariant

In this paper we introduce a novel method of fingerprint alignment that uses the intrinsic geometric properties of minutiae-based triangles combined with the geometric invariant. The minutiae points are extracted from the fingerprint image and a Delaunay (DL) triangulation is constructed from these minutiae points resulting in a series of triangles. Corresponding minutiae points are established using local affine invariants constructed from the local minutia-based triangles. Triangles that are distorted by noise or have no counter part on the query are discarded. We rely only on “strong” matches that are reliable and present, for example, where the error metric between the local absolute invariants is below a set threshold. The correspondences of such matches are then used to estimate transformation parameters. The performance of our method is represented by computing the distance map error between a template and a query fingerprint after undoing the transformation, computed from the ridge structures of the two fingerprints. In conclusion, the proposed method can be used to find the corresponding minutiae and align any fingerprints considered into affine transformation, in the presence of noise including the partial occlusion

Classification of the stages of hyperplasia in breast ducts by analyzing different depths and segmentation of ultrasound breast scans into ductal areas

Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, pp. 2396-2399.In this paper, we study in depth the potential of detection of epithelium hyperplastic growth in the breast ducts leading to early breast cancer detection. Towards that end, we use a stochastic decomposition algorithm of the RF echo into its coherent and diffuse components that yields image parameters related to the structural parameters of the hyperplastic stages of the breast tissue. Previously, we proved that the two parameters, in particular the number of coherent scatterers and the Rayleigh scattering degree show very high ability to discriminate between various stages of hyperplasia even in cases of low resolution and low SNR values. In this paper, the discrimination power of the other parameters is studied further considering different depths using a point scatterer model simulator that mimics epithelium hyperplastic growth in the breast ducts. Significant improvement is obtained in the performance with the newly adopted method considering depth. Values of Az up to 0.974 are obtained when discriminating between pairs of stages using the parameter residual error variance. In addition, this paper presents a fast nonparametric segmentation procedure to locate the ducts illustrated using phantom data. The performance of the segmentation procedure is obtained as Az>0.948 for various regions of breast scans