Improved Depth Map Estimation from Stereo Images based on Hybrid Method

In this paper, a stereo matching algorithm based on image segments is presented. We propose the hybrid segmentation algorithm that is based on a combination of the Belief Propagation and Mean Shift algorithms with aim to refine the disparity and depth map by using a stereo pair of images. This algorithm utilizes image filtering and modified SAD (Sum of Absolute Differences) stereo matching method. Firstly, a color based segmentation method is applied for segmenting the left image of the input stereo pair (reference image) into regions. The aim of the segmentation is to simplify representation of the image into the form that is easier to analyze and is able to locate objects in images. Secondly, results of the segmentation are used as an input of the local window-based matching method to determine the disparity estimate of each image pixel. The obtained experimental results demonstrate that the final depth map can be obtained by application of segment disparities to the original images. Experimental results with the stereo testing images show that our proposed Hybrid algorithm HSAD gives a good performance

Acellular oxidative potential assay for screening of amorphous silica nanoparticles.

Rapid acellular screening of amorphous silica nanoforms of different sizes and surface modifications for their oxidative potential

Contrasting biological potency of particulate matter collected at sites impacted by distinct industrial sources

Association of biological effects in A549 cells with metal content in size-fractionated particles. Cytotoxic potencies according to lactate dehydrogenase (LDH) release and resazurin reduction were regressed against total, water-soluble, and non-water-soluble metals. Pearson product–moment correlation coefficient r-values are presented. LDH release. A) Total metals. UFP, r = 0.77, p = 0.13; PM0.1–2.5, r = −0.55, p = 0.34; PM2.5–10, r = 0.32, p = 0.60; PM>10, r = −0.68, p = 0.21. B) Water-soluble metals. UFP, r = 0.51, p = 0.38; PM0.1–2.5, r = −0.64, p = 0.25; PM2.5–10, r = −0.35, p = 0.57; PM>10, r = −0.68, p = 0.20. C) Non-water-soluble metals. UFP, r = 0.75, p = 0.14; PM0.1–2.5, r = −0.46, p = 0.43; PM2.5–10, r = 0.36, p = 0.55; PM>10, r = −0.68, p = 0.21. Resazurin reduction. D) UFP, r = −0.19, p = 0.76; PM0.1–2.5, r = −0.63, p = 0.26; PM2.5–10, r = −0.60, p = 0.28; PM>10,r = 0.18, p = 0.78. Water-soluble metals. UFP, r = −0.20, p = 0.74; PM0.1–2.5, r = −0.41, p = 0.49; PM2.5–10, r = −0.09, p = 0.88; PM>10, r = 0.04, p = 0.95. Non-water-soluble metals. UFP, r = −0.12, p = 0.84; PM0.1–2.5, r = −0.65, p = 0.24; PM2.5–10, r = −0.62, p = 0.26; PM>10, r = 0.18, p = 0.77. (PDF 43 kb

Synthesis and Physicochemical Characterization of Mesoporous S

There exists a knowledge gap in understanding potential toxicity of mesoporous silica nanoparticles. A critical step in assessing toxicity of these particles is to have a wide size range with different chemistries and physicochemical properties. There are several challenges when synthesizing mesoporous silica nanoparticles over a wide range of sizes including (1) nonuniform synthesis protocols using the same starting materials, (2) the low material yield in a single batch synthesis (especially for particles below 60–70 nm), and (3) morphological instability during surfactant removal process and surface modifications. In this study, we synthesized a library of mesoporous silica nanoparticles with approximate particle sizes of 25, 70, 100, 170, and 600 nm. Surfaces of the silica nanoparticles were modified with hydrophilic-CH2–(CH2)2–COOH and relatively hydrophobic-CH2–(CH2)10–COOH functional groups. All silica nanoparticles were analysed for morphology, surface functionality, surface area/pore volume, surface organic content, and dispersion characteristics in liquid media. Our analysis revealed the synthesis of a spectrum of monodisperse bare and surface modified mesoporous silica nanoparticles with a narrow particle size distribution and devoid of cocontaminants critical for toxicity studies. Complete physicochemical characterization of these synthetic mesoporous silica nanoparticles will permit systematic toxicology studies for investigation of structure-activity relationships

Hybrid method of 3-D image reconstruction from stereo pictures

A hybrid method of 3-D image reconstruction from stereo pictures is introduced. The proposed method utilizes the modified algorithm SAD where Depth map is calculated from 3-D noisy Cost function, which is de-noised by a new de-noising technique with block-matching and 3-D filtering. A technique of Epipolar geometry is then applied to stereo pictures. False corner matches in stereo pictures are discarded by comparing their position with the Depth map. The resulting correct corner matches are used to calculate a final Fundamental matrix F by a linear method and its Error matrix is utilized to correct great errors in the final Depth map. The method successfully improves results of 3-D image reconstruction in comparison with SAD or Correlation algorithms

Oligonucleotide microarray analysis of chromosome 17 gene expression in a model human epithelial ovarian cancer cell line, TOV112D, and in epithelial ovarian tumors and ovarian malignant ascites

The importance of developing relevant ovarian cancer models led us to test the applicability of a system comprised of epithelial ovarian cancer cell lines. The high frequency of loss of heterozygosity (LOH) and rearrangements of chromosome 17 in ovarian tumors provide evidence of a role of chromosome 17 genes in ovarian tumorigenesis. Oligonucleotide microarray expression analysis was applied to assess the expression profiles of 864 probe sets that map to chromosome 17. The TOV112D ovarian cancer cell line, a spontaneously immortalized and tumorigenic ovarian cancer cell line derived from an endometrioid histopathological subtype, which has been shown to exhibit LOH of chromosome 17, was used as a model to identify candidate genes based on Affymetrix expression microarray analyses in comparative analysis with three primary cultures derived from normal ovarian surface epithelium (NOSE). Two-way comparative analyses identified 81 probe sets, representing 64 differentially expressed genes, which exhibited at least a three-fold difference in expression relative to the mean of NOSE samples. The expression of these 64 candidate genes was investigated by microarray analysis in 31 fresh solid malignant ovarian tumors of different histopathologies, six ovarian tumors of borderline pathology, 32 primary cultures of ovarian tumors, 28 primary cultures of malignant ovarian ascites, and 16 NOSE samples. The chromosome 17 expression profile of TOV112D monolayer was compared with this cell line grown as a three-dimensional spheroid, solid tumors and monolayer cultures of these tumors from intraperitoneal and subcutaneous injection into nude mice. The expression profiles of selected candidates were validated by RT-PCR. About 63% of the candidates overexpressed at least three-fold relative to TOV112D were also overexpressed in some of the solid malignant ovarian tumors, and about 91% of the candidates that were underexpressed at least three-fold in TOV112D were also underexpressed in some of these tumors. The same differential pattern of gene expression of candidates was also observed in primary cultures of ovarian tumors and ovarian ascites, however, the effect in primary cultures was reduced. These results indicate that TOV112D, representing a spontaneously immortalized long-term passage, was more representative of solid ovarian tumors compared with the primary cultures. Growth conditions showed little impact on the expression profile of candidates when TOV112D was grown in different culture environments such as in vitro monolayer or mouse tumor xenograft. The finding that TOV112D identified differentially expressed genes in ovarian tumor samples regardless of histopathological subtype indicates that it is a useful model, not only to study the endometrioid subtype, but also serous and clear cell subtypes of epithelial ovarian cancer. Comparison of the expression profiles of our candidate genes identified by microarray analysis with published reports revealed that eight genes (ACACA, SFRS2, CCL2, CSF3, IGFBP4, KRT19, ITGA3, and TIMP2) were previously implicated in ovarian cancer, and 23 including MAC30 and TBX2 were implicated in tumorigenesis of other types of cancers. The use of long-term ovarian cancer cultures provides scientists with a model to study candidate genes, some of which may prove important for early detection or represent targets for the development of new ovarian cancer treatments

Optimal and Quasioptimal Algorithms of Distinction of the Compressed Images in Bases of Orthogonal Polynomials

The synthesis and analysis of effective practically realized algorithms of distinction of signals and images represented in bases of orthogonal polynomials was executed. Influence of distortions at formation of sensed and reference useful signals was considered. Recommendations about application of the synthesized distinction algorithms were formulated

Restoration of Deterministic and Interference Distorted Signals and Images with Use of the Generalized Spectra Based on Orthogonal Polynomials and Functions

Restoration algorithms of signals and images on the basis of their generalized spectra in bases of orthogonal polynomials and functions at absence and presence of random distortions have been examined. It is shown that in absence of hindrances the number of coefficients of the generalized spectrum of a restored signal (image) is determined by the desired approximation error at use of one or another metrics of functional space. If hindrances take place then there is an optimum number of coefficients of the generalized spectrum for signal (image) restoration. Working data of the proposed algorithms for various types of useful signals have been illustrated