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      Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing

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          Abstract

          Ultrasound examination (US) does a key role in the diagnosis and management of the patients with clinically suspected appendicitis which is the most common abdominal surgical emergency. Among the various sonographic findings of appendicitis, outer diameter of the appendix is most important. Therefore, clear delineation of the appendix on US images is essential. In this paper, we propose a new intelligent method to extract appendix automatically from abdominal sonographic images as a basic building block of developing such an intelligent tool for medical practitioners. Knowing that the appendix is located at the lower organ area below the bottom fascia line, we conduct a series of image processing techniques to find the fascia line correctly. And then we apply fuzzy ART learning algorithm to the organ area in order to extract appendix accurately. The experiment verifies that the proposed method is highly accurate (successful in 38 out of 40 cases) in extracting appendix.

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          A review on image segmentation techniques

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            Neural networks for pattern recognition

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              Appendicitis: evaluation of sensitivity, specificity, and predictive values of US, Doppler US, and laboratory findings.

              To evaluate the sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of ultrasonography (US), Doppler US, and laboratory findings in the diagnosis of appendicitis. A total of 125 consecutive patients suspected of having appendicitis were prospectively included for US appendiceal (diameter enlarged to 6 mm or greater, intraluminal fluid, lack of compressibility) and periappendiceal (periileal inflammatory changes, cecal wall thickening, periileal lymph nodes, peritoneal fluid) evaluation, Doppler US evaluation (appendiceal wall signal), and laboratory assessment (leukocytosis, C-reactive protein [CRP]). Definite diagnoses were established at surgery in 61 patients, at endoscopy with biopsy in two patients, and at clinical follow-up in 62 patients. The prevalence of appendicitis was 46%. The appendix was identified with US in 86% of the patients, which included 96% of patients with and 72% of patients without appendicitis. The most accurate appendiceal finding for appendicitis was a diameter of 6 mm or larger, with a sensitivity, specificity, NPV, and PPV of 98%. The lack of visualization of the appendix with US had an NPV of 90%. The most accurate periappendiceal finding of appendicitis was the presence of inflammatory fat changes, with an NPV of 91% and a PPV of 76%, whereas other findings had both NPV and PPV less than 65%. An increase in both white blood cell (WBC) count and CRP level had a PPV of 71%, whereas combined normal WBC count and CRP value had an NPV of 84%. A threshold 6-mm diameter of the appendix under compression is the most accurate US finding for appendicitis and has high NPV and PPV. Copyright RSNA, 2003
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                Author and article information

                Journal
                Comput Math Methods Med
                Comput Math Methods Med
                CMMM
                Computational and Mathematical Methods in Medicine
                Hindawi Publishing Corporation
                1748-670X
                1748-6718
                2015
                18 May 2015
                : 2015
                : 389057
                Affiliations
                1Department of Computer Engineering, Silla University, Busan 617-736, Republic of Korea
                2Department of Computer Engineering, Pusan National University, Busan 609-735, Republic of Korea
                3Department of Computer Games, Yong-In Songdam College, Yongin 449-040, Republic of Korea
                4Department of Radiology, Inje University Busan Paik Hospital, Busan 614-735, Republic of Korea
                Author notes
                *Kwang Baek Kim: gbkim@ 123456silla.ac.kr and

                Academic Editor: Kevin Ward

                Author information
                http://orcid.org/0000-0001-9475-8223
                http://orcid.org/0000-0003-1365-0232
                Article
                10.1155/2015/389057
                4450307
                26089963
                8ebc9469-8b0f-453f-b61c-b82953f3eeb7
                Copyright © 2015 Kwang Baek Kim et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 July 2014
                : 19 September 2014
                : 26 September 2014
                Categories
                Research Article

                Applied mathematics
                Applied mathematics

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