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This paper proposes a novel hyperspectral matching technique by integrating the Jeffries-Matusita measure (JM) and the Spectral Angle Mapper (SAM) algorithm. The deterministic Spectral Angle Mapper and stochastic Jeffries-Matusita measure are orthogonally projected using the sine and tangent functions to increase their spectral ability. The developed JM-SAM algorithm is implemented in effectively discriminating the landcover classes and cover types in the hyperspectral images acquired by PROBA/CHRIS and EO-1 Hyperion sensors. The reference spectra for different land-cover classes were derived from each of these images. The performance of the proposed measure is compared with the performance of the individual SAM and JM approaches. From the values of the relative spectral discriminatory probability (RSDPB) and relative discriminatory entropy value (RSDE), it is inferred that the hybrid JM-SAM approach results in a high spectral discriminability than the SAM and JM measures. Besides, the use of the improved JM-SAM algorithm for supervised classification of the images results in 92.9% and 91.47% accuracy compared to 73.13%, 79.41%, and 85.69% of minimum-distance, SAM and JM measures. It is also inferred that the increased spectral discriminability of JM-SAM measure is contributed by the JM distance. Further, it is seen that the proposed JM-SAM measure is compatible with varying spectral resolutions of PROBA/CHRIS (62 bands) and Hyperion (242 bands). [ABSTRACT FROM AUTHOR]

This paper reports the results of a study to differentiate iron ores in terms of their grades, using the hyperspectral (EO-1 Hyperion) image data, covering a mineralized belt in the Noamundi area, eastern India. The study involves hyperspectral data collection, pre-processing (reduction of atmospheric and solar flux effects), generation of spectral curves from the image for the iron ore deposits, extraction of key spectral parameters and linear spectral unmixing for mapping iron ore abundance. Spectral curves for iron ore deposits extracted from the Hyperion image pixels exhibit strong absorption at 850–900 nm and 2150–2250 nm wavelengths, which is typical of iron ores. The strength of the absorption features in the continuum removed spectra varies spatially in the image around the mining areas, indicating differences in composition/grade of the iron ores. Spectral parameters such as the depth, width, area and wavelength position of the absorption features, derived from image spectra in the 850–900 nm and 2150–2250 nm regions, correlate well with the concentration of iron-oxide and alumina (gangue) in the ore samples obtained from the mine face. Well defined correlations are evident between the concentration of iron oxide and (i) the depth of NIR absorption feature ( R 2 = 0.883); (ii) the width of NIR absorption feature ( R 2 = 0.912); and (iii) the area of the NIR absorption feature and ( R 2 = 0.882). Further, the linear spectral unmixing resulted in an iron ore abundance map which, in conjunction with the image- and laboratory-spectra, helped in assessing the grades of iron ores in the study area. Thus, this study demonstrates the feasibility of discriminating grades of iron ores based on spectral information derived from spaceborne hyperspectral imagery. [ABSTRACT FROM AUTHOR]

B Presenter: b Srinivas Sanjeevi MD | University of Texas Health Science Center at Houston B Background: b Studies have demonstrated a modest survival benefit amongst hepatocellular carcinoma (HCC) patients treated with yittrium-90 radioembolization (RE). We hypothesize that a RE survival benefit versus chemotherapy may be influenced by cirrhosis. B Conclusion: b Using this model yittrium-90 radioembolization resulted in a modest survival increase for patients with higher MELD scores. [Extracted from the article]

Lunar surface exploration is increasing rapidly. These exploring satellites provide a large number of high resolution images containing topographical information. The topographical information in lunar surface are craters, ridges, mountains and grabens. Extracting this topographical information manually is time-consuming. Hence, an automatic feature extraction is favored. This paper presents a novel approach using image processing techniques to automatically detect ridges in lunar images. The approaches adopted for this development includes phase symmetry, phase congruency and morphological operations to automatically detect significant ridges. The phase symmetry extracts symmetry features with discontinuities, phase congruency extracts features lying in low contrast regions and morphological operations such as thinning and pruning are used to obtain significant ridges. The proposed novel approach experiments on a test set of different regions. These different region images are obtained from different sensors (LROC, Selene and Clementine) having different spatial resolution and illumination variation. The results obtained are compared with the plan curvature method; and they are evaluated based on true and false detection of ridge pixels. Irrespective of illumination variation and spatial resolution, the proposed approach provides better results than the plan curvature method and its detection rate is approximately 92%. [ABSTRACT FROM AUTHOR]

Abstract: Lunar craters provide ample opportunities to study and understand crater morphology because of their vast numbers. This paper focuses on the topographical mapping of 33 Mare craters (Flat- and Round-floor) of ∼2km diameter, using the SELENE DTM. Each crater was analyzed individually for its slope, regional topography and rim signature. The crater slope analysis revealed a small slope variation between the flat- and round-floor craters, in a similar diameter range, with some overlap between them. In the regional topographical analysis, the impact craters formed on the flat- and sloped-surface were analyzed in detail. The crater profile extracted through the rim crest was compared with its corresponding regional topographic profile (obtained over ∼3crater radii). Four types of crater occurrences were observed: type i, ii and iv craters were formed on sloped surface, whereas type iii craters are formed on a flat surface with an equally raised rim. The occurrences of the rim crest on type i and ii craters are on the topographically elevated side of the terrain. But in type iv craters, the rim crest occurs on the topographically lower side of the terrain. The type iv craters uplifted the topographically lower terrain, which depicts the alteration that had taken place due to the impact. This topographical analysis suggests that the surrounding topography should also be considered for understanding the craters. Finally, from the crater rim signature analysis, it was evident that the prominent V-shaped incisions on the rim are caused due to landslide/slumping and by small impactors. This DTM based simple lunar crater analysis revealed information about the crater association with their surrounding topography and their morphological variations on flat- and sloped- surface. [Copyright &y& Elsevier]

The article focuses on the complications of biliary anastomotic strictures (BAS) post pancreaticoduodenectomy (PD), and talks of study conducted by Johns Hopkins University School of Medicine, development of postoperative pancreatic fistula (POPF), and independent predictors such as jaundice.