1,720,975 research outputs found
Supplementary_File_794158 - Cellulite Reduction by Modified Thai Herbal Compresses; A Randomized Double-Blind Trial
No full textSupplementary_File_794158 for Cellulite Reduction by Modified Thai Herbal Compresses; A Randomized Double-Blind Trial by Ngamrayu Ngamdokmai, Neti Waranuch, Krongkarn Chootip, Katechan Jampachaisri, C. Norman Scholfield, and Kornkanok Ingkaninan in Journal of Evidence-Based Integrative Medicine</p
Thresholding wavelet coefficients of the IUWT.
No full text<p>(A) The sum of wavelet levels 2 and 3. (B) A threshold was applied to A to identify the lowest 15% of wavelet coefficients within the FOV. (C) A cleaner version of the segmentation in B, created by removing connected objects and filling holes with areas smaller than 75 and 20 pixels respectively. (D) A hand-segmented image from the DRIVE database, shown for reference.</p
Application of vessel detection to REVIEW database images.
No full text<p>(A–C) Vessels detected in example images from the CLRIS, HRIS and VDIS respectively. (D) Individual diameters found for a vessel in a KPIS image. Note that in the KPIS image, the visible branching vessels are much narrower and dimmer in comparison to the main vessel, so that they occur as unconnected objects in the segmented image. This difference in contrast then allows edges still to be found for the main vessel at these branching locations.</p
Overview of the main steps taken by our algorithm when processing a fundus image.
No full text<p>(A) The image (here, from the DRIVE database) is read. (B) The green channel is selected for later processing. (C) A mask is produced by thresholding. (D) The IUWT is applied to B. (E) Wavelet coefficients are thresholded. (F) Small objects are removed and holes are filled in E. (G) Morphological thinning is applied to F. (H) The distance transform is applied to F to assist with estimating diameters and removing erroneously detected segments. (I) Branches are removed from G and spline fitting applied to determine centrelines. (J) Edges are detected perpendicular to the centrelines.</p
Determining vessel edges by zero-crossings.
No full text<p>(A) A ‘straightened’ vessel image, created by stacking many image profiles alongside one another. (B) Corresponding stacked profiles determined from the initially-segmented image. White pixels belong to the vessel under consideration, while gray pixels belong to other detected vessels. An initial vessel width estimate is determined from the median of the sum of white pixels on each row, and refined using the averaged profile in F. (C) The profiles in A after smoothing with an anisotropic Gaussian filter, and subsequently applying a second filter to approximate the second derivative computed perpendicular to the vessel (i.e. horizontally). In this representation most of the vessel consists of negative values, but the central light reflex contains positive values. (D) Pixels in C representing positive-to-negative (red) and negative-to-positive (blue) transitions. Transitions corresponding to the second vessel region in B are removed. The length of each connected line is computed, and only the longest lines that fall close to the estimated vessel boundaries are retained. (E) The edges identified by the algorithm, superimposed on top of the straighted vessel. (F) A mean vessel profile, computed by averaging all the profiles in A, excluding pixels belonging to other vessels. The locations of the maximum and minimum gradients to the left and right of centre are shown in blue. The transitions in D are removed if they do not fall close to these locations, and the distance between them is also used when calculating the Gaussian filter sizes. (G) The edges identified by the algorithm, shown on the original image from the REVIEW database.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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