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      Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

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          Abstract

          Currently, diagnosis of skin diseases is based primarily on the visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide objective information to support clinical decision-making. Noninvasive skin imaging techniques provide complementary information to the clinician. In recent years, optical coherence tomography (OCT) has become a powerful skin imaging technique. According to specific functional needs, skin architecture varies across different parts of the body, as do the textural characteristics in OCT images. There is, therefore, a critical need to systematically analyze OCT images from different body sites, to identify their significant qualitative and quantitative differences. Sixty-three optical and textural features extracted from OCT images of healthy and diseased skin are analyzed and, in conjunction with decision-theoretic approaches, used to create computational models of the diseases. We demonstrate that these models provide objective information to the clinician to assist in the diagnosis of abnormalities of cutaneous microstructure, and hence, aid in the determination of treatment. Specifically, we demonstrate the performance of this methodology on differentiating basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) from healthy tissue.

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          Most cited references35

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          A tutorial on support vector regression

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            Nephrogenic systemic fibrosis: suspected causative role of gadodiamide used for contrast-enhanced magnetic resonance imaging.

            Nephrogenic systemic fibrosis is a new, rare disease of unknown cause that affects patients with renal failure. Single cases led to the suspicion of a causative role of gadodiamide that is used for magnetic resonance imaging. This study therefore reviewed all of the authors' confirmed cases of nephrogenic systemic fibrosis (n = 13) with respect to clinical characteristics, gadodiamide exposure, and subsequent clinical course. It was found that all had been exposed to gadodiamide before the development of nephrogenic systemic fibrosis. The delay from exposure to first sign of the disease was 2 to 75 d (median 25 d). Odds ratio for acquiring the disease when gadodiamide exposed was 32.5 (95% confidence interval 1.9 to 549.2; P < 0.0001). Seven (54%) patients became severely disabled, and one died 21 mo after exposure. No other exposure/event than gadodiamide that was common to more than a minority of the patients could be identified. These findings indicate that gadodiamide plays a causative role in nephrogenic systemic fibrosis.
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              Optical coherence tomography (OCT): a review

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                Author and article information

                Contributors
                mrn.avanaki@wayne.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 December 2017
                20 December 2017
                2017
                : 7
                : 17912
                Affiliations
                [1 ]ISNI 0000 0001 1456 7807, GRID grid.254444.7, Biomedical Engineering Department, , Wayne State University, ; Detroit, MI USA
                [2 ]ISNI 0000000121622106, GRID grid.8509.4, Applied Electronics Department, , Roma Tre University, ; Rome, Italy
                [3 ]ISNI 0000 0001 0740 9747, GRID grid.412553.4, Department of Electrical Engineering, , Sharif University of Technology, ; Tehran, Iran
                [4 ]ISNI 0000 0001 1456 7807, GRID grid.254444.7, Department of Dermatology, , Wayne State University School of Medicine, ; Detroit, MI USA
                [5 ]ISNI 0000 0001 1456 7807, GRID grid.254444.7, Barbara Ann Karmanos Cancer Institute, ; Detroit, MI USA
                Article
                17398
                10.1038/s41598-017-17398-8
                5738372
                29263332
                78f21c8a-ab8d-4c17-a01b-198045e006ba
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 May 2017
                : 10 November 2017
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