Search results for " Detection"

The iterative object symmetry transform

2005

This paper introduces a new operator named the Iterated Object Transform that is computed by combining the Object Symmetry Transform with the morphological operator erosion. This new operator has been applied on both binary and gray levels images showing the ability to grasp the internal structure of a digital object. We present some experiments on real images in face analysis.

Update on biomarkers for the detection of lung cancer

2017

Patients at risk for lung cancer may have subclinical disease for years before presentation. The diagnosis of this disease is primarily based on symptoms, and detection often occurs after curative intervention is no longer possible. At present, no lung cancer early-detection biomarker is clinically available. This study reviews the most recent advances in early detection and molecular diagnostic biomarkers for the detection of lung cancer. This review includes an overview of the various biological specimens and matrices in which these biomarkers could be analyzed, as well as the diverse strategies and approaches for identifying new biomarkers that are currently being explored. Several novel…

“The risk of age”? Early detection test, prostate cancer and practices of self

2010

Abstract Drawing on Rose and Novas’s concept of “biological citizenship” and Michel Foucault's "practices of self", this paper reflects on how men become agents of their own therapeutic regimens, and yet internalise messages of risk and practices of self within early detection of prostate cancer discourses in the late 20th century. In doing so, it traces the ways in which concepts of age, gender and risk converge at the problematic site of prostate cancer and preventative health strategies, both of the state and the medical profession. Analysing how insecurities have simultaneously resulted in over-promoting and over-diagnosing risk, thereby blurring the lines between normal and pathologica…

FAST EDGE-FILTERED IMAGE UPSAMPLING.

2011

We present a novel edge preserved interpolation scheme for fast upsampling of natural images. The proposed piecewise hyperbolic operator uses a slope-limiter function that conveniently lends itself to higher-order approximations and is responsible for restricting spatial oscillations arising due to the edges and sharp details in the image. As a consequence the upsampled image not only exhibits enhanced edges, and discontinuities across boundaries, but also preserves smoothly varying features in images. Experimental results show an improvement in the PSNR compared to typical cubic, and spline-based interpolation approaches.

A family of kernel anomaly change detectors

2014

This paper introduces the nonlinear extension of the anomaly change detection algorithms in [1] based on the theory of reproducing kernels. The presented methods generalize their linear counterparts, under both the Gaussian and elliptically-contoured assumptions, and produce both improved detection accuracies and reduced false alarm rates. We study the Gaussianity of the data in Hilbert spaces with kernel dependence estimates, provide low-rank kernel versions to cope with the high computational cost of the methods, and give prescriptions about the selection of the kernel functions and their parameters. We illustrate the performance of the introduced kernel methods in both pervasive and anom…

Modified LACIF filtering in background disjoint noise

2011

Abstract This work deals with pattern recognition methods based on correlations for images in the presence of noise. We propose a modification of the nonlinear Locally Adaptive Contrast Invariant Filter (LACIF) that yields correlation peaks that are invariant to linear intensity changes of the target but that has some limitations in the presence low variance nonoverlapping background noise. The modification of the filter implies a normalization by a global variance of several distributions. The estimation of the variance distributions is done locally by means of correlations. Experimental results as well as comparisons with the classical matched filter and the common LACIF are given.

Development of a multispectral imagery device devoted to weed detection

2003

Multispectral imagery is a large domain with number of practical applications: thermography, quality control in industry, food science and agronomy, etc. The main interest is to obtain spectral information of the objects for which reflectance signal can be associated with physical, chemical and/or biological properties. Agronomic applications of multispectral imagery generally involve the acquisition of several images in the wavelengths of visible and near infrared. This paper will first present different kind of multispectral devices used for agronomic issues and will secondly introduce an original multispectral design based on a single CCD. Third, early results obtained for weed detection…

Pretreatment T790M mutation detection by ultrasensitive PCR assay as predictor of efficacy in non-small lung cancer (NSCLC) patients treated with 1st…

2019

Performances of the Fault Decoupling Device when unbalanced and multiple faults occur on distribution systems.

2005

Nowadays industrial processes are largely based on electronic devices such as programmable logic controllers and adjustable speed drives. Consequently, industrial equipments became less tolerant towards power supply disturbances. Voltage dips due to faults are surely among the worst disturbances for industrial equipments. A paper machine can be affected by disturbances of only 10% voltage drop lasting for 100 ms. A voltage dip of 75% (of the nominal voltage) with a duration shorter than 100 ms results in material loss in the range of thousands of US Dollars for semiconductors industry [1].

Intratumoral Heterogeneity, Its Contribution to Therapy Resistance and Methodological Caveats to Assessment

2014

Cancer is one of the most urgent health issues of today. According to WHO, the number of cancer cases is expected to increase by 75% in the next two decades (1). Despite some remarkable achievements in the fields of cancer prevention and early detection, the goal of developing effective anti-cancer therapies still remains unmet. Tumor recurrence due to treatment resistance is the most common cause of death from cancer. Delineating cellular and molecular mechanisms underlying tumor recurrence is of prime importance for the ability to improve the efficacy of existing therapies and develop new strategies to cancer treatment.