Automated diagnosis of celiac disease by video capsule endoscopy using DAISY Descriptors.
Celiac disease is a genetically determined disorder of the small intestine, occurring due to an immune response to ingested gluten-containing food. The resulting damage to the small intestinal mucosa hampers nutrient absorption, and is characterized by diarrhea, abdominal pain, and a variety of extr...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 6; pp. 1 - 10 |
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| Autores principales: | , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136503263&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136503263 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jun2019 vid: 43 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 136503263 136503263 136503263 10.1007/s10916-019-1285-6 136503263 ppf: 1 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automated diagnosis of celiac disease by video capsule endoscopy using DAISY Descriptors. aug: au: Vicnesh, Jahmunah Wei, Joel Koh En Oh, Shu Lih Acharya, U. Rajendra Ciaccio, Edward J. Lewis, Suzanne K. Green, Peter H. Bhagat, Govind affil: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore, Singapore sug: subj: Celiac Disease Diagnosis Capsule Endoscopy Methods Videorecording Diagnosis, Computer Assisted Human Algorithms Physics Descriptive Statistics Sensitivity and Specificity Predictive Value of Tests Celiac Disease Symptoms Academic Medical Centers Duodenum Pathology Intestine, Small Pathology Image Processing, Computer Assisted Methods Celiac Disease Etiology ab: Celiac disease is a genetically determined disorder of the small intestine, occurring due to an immune response to ingested gluten-containing food. The resulting damage to the small intestinal mucosa hampers nutrient absorption, and is characterized by diarrhea, abdominal pain, and a variety of extra-intestinal manifestations. Invasive and costly methods such as endoscopic biopsy are currently used to diagnose celiac disease. Detection of the disease by histopathologic analysis of biopsies can be challenging due to suboptimal sampling. Video capsule images were obtained from celiac patients and controls for comparison and classification. This study exploits the use of DAISY descriptors to project two-dimensional images onto one-dimensional vectors. Shannon entropy is then used to extract features, after which a particle swarm optimization algorithm coupled with normalization is employed to select the 30 best features for classification. Statistical measures of this paradigm were tabulated. The accuracy, positive predictive value, sensitivity and specificity obtained in distinguishing celiac versus control video capsule images were 89.82%, 89.17%, 94.35% and 83.20% respectively, using the 10-fold cross-validation technique. When employing manual methods rather than the automated means described in this study, technical limitations and inconclusive results may hamper diagnosis. Our findings suggest that the computer-aided detection system presented herein can render diagnostic information, and thus may provide clinicians with an important tool to validate a diagnosis of celiac disease. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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