Well-defined relationships between oligonucleotide properties and hybridization signal intensities (HSI) can aid chip design, data normalization and true biological knowledge discovery. We clarify these relationships using the data from two microarray experiments containing over three million probes from 48 high-density chips. We find that melting temperature (T(m)) has the most significant eff...

We present a framework for hyperspectral image (HSI) analysis validation, specifically abundance fraction estimation based on HSI measurements of water soluble dye mixtures printed on microarray chips. In our work we focus on the performance of two algorithms, the Least Absolute Shrinkage and Selection Operator (LASSO) and the Spatial LASSO (SPLASSO). The LASSO is a well known statistical metho...

This paper presents a hierarchical deep framework called Spectral-Spatial Response (SSR) to jointly learn spectral and spatial features of Hyperspectral Images (HSIs) by iteratively abstracting neighboring regions. SSR forms a deep architecture and is able to learn discriminative spectral-spatial features of the input HSI at different scales. It includes several existing spectral-spatial-based ...

Characterization of the joint (among wavebands) probability density function (pdf) of hyperspectral imaging (HSI) data is crucial for several applications, including the design of constant false alarm rate (CFAR) detectors and statistical classifiers. HSI data are vector (or equivalently multivariate) data in a vector space with dimension equal to the number of spectral bands. As a result, the ...

BACKGROUND The Fagerström Test for Nicotine Dependence (FTND) is used for assessing nicotine dependence. A shorter test derived from the FTND used for the general population is the Heavy Smoking Index (HSI) (six questions vs. two). The objective of this study is to compare the validity of the HSI versus the FTND. METHODS A survey of tobacco use in the general population was carried out in the...

This paper proposes a novel method of segment-tree filtering to improve the classification accuracy of hyperspectral image (HSI). Segment-tree filtering is a versatile method that incorporates spatial information and has been widely applied in image preprocessing. However, to use this powerful framework in hyperspectral image classification, we must reduce the original feature dimensionality to...

Displaying the large number of bands in a hyperspectral image (HSI) on a trichromatic monitor has been an active research topic. The visualized image shall convey as much information as possible from the original data and facilitate image interpretation. Most existing methods display HSIs in false colors, which contradict with human’s experience and expectation. In this paper, we propose a nonl...

This paper presents a novel hyperspectral feature-extraction toolkit that provides a simple, automated, and accurate approach to materials classification from hyperspectral imagery (HSI). The proposed toolkit is built as an extension to the state-of-the-art technology in automated feature extraction, the Feature Analyst software suite. Feature Analyst uses, along with spectral information, feat...

Due to escalating conflicts and resultant economic constraints, different social services in low income and low-middle income countries have witnessed a decline in its standards, and increase in the costs. This situation has led to emergence of large numbers of patients and their families who cannot afford the costs of health services provided by public hospitals. On this background, and the ol...