Identification of intestinal wall abnormalities and ischemia by modeling spatial uncertainty in computed tomography imaging findings

Computer Methods and Programs in Biomedicine

Volumn 117, Issue 1, 2014, Pages 30-39

  Tsunoyama, Taichiro ^a   Pham, Tuan D ^b   Fujita, Takashi ^a   Sakamoto, Tetsuya ^a  

^a TEIKYO UNIVERSITY   (Japan)

^b UNIVERSITY OF AIZU   (Japan)

Author keywords

Computed tomography; Fuzzy entropy; Indicator kriging; Intestinal abnormalities; Intestinal ischemia; Pattern classification

Indexed keywords

DIAGNOSIS; FEATURE EXTRACTION; MAPPING; PATTERN RECOGNITION; UNCERTAINTY ANALYSIS;

AUTOMATED IDENTIFICATION; DIAGNOSTIC PERFORMANCE; FUZZY ENTROPY; GASTROINTESTINAL DISORDERS; IMAGE FEATURE EXTRACTIONS; INDICATOR KRIGING; INTESTINAL ABNORMALITIES; INTESTINAL ISCHEMIA;

COMPUTERIZED TOMOGRAPHY;

ADULT; AGED; ARTICLE; ASCENDING COLON; CLINICAL ARTICLE; COLON ISCHEMIA; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; DESCENDING COLON; FEMALE; HEMICOLECTOMY; HUMAN; ILEUM; INTESTINE ISCHEMIA; INTESTINE WALL; MALE; SMALL INTESTINE RESECTION; SUPERIOR MESENTERIC ARTERY; UNCERTAINTY; VERY ELDERLY; BIOLOGICAL MODEL; INTESTINE; MIDDLE AGED; PROCEDURES; RADIOGRAPHY;

ADULT; AGED; FEMALE; HUMANS; INTESTINES; MIDDLE AGED; MODELS, BIOLOGICAL; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84906933772     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2014.05.003     Document Type: Article

References (41)

1. Feldman M., Friedman L.S., Brandt L.J. Sleisinger and Fordtran's Gastrointestinal and Liver Disease: Pathology, Diagnosis, Management 2010, Saunders, Philadelphia, PA. 9th ed.
2. Goldman L., Schafer A.I. Goldman's Cecil Medicine 2012, Saunders, Philadelphia, PA. 24th ed.
3. Mayo Clinic Mayo Clinic Family Health Book 2009, Oxmoor House, Birmingham, AL. 4th ed.
4. Flores J.O. Small intestine biopsy. Gale Encyclopedia of Medicine 2002, http://www.healthline.com/galecontent/small-intestine-biopsy#1.
5. Ciaccio E.J., Tennyson C.A., Lewis S.K., Krishnareddy S., Bhagat G., Green P.H.R. Distinguishing patients with celiac disease by quantitative analysis of videocapsule endoscopy images. Comput. Methods Programs Biomed. 2010, 100:39-48.
6. Ciaccio E.J., Tennyson C.A., Bhagat G., Lewis S.K., Green P.H.R. Transformation of videocapsule images to detect small bowel mucosal differences in celiac versus control patients. Comput. Methods Programs Biomed. 2012, 108:28-37.
7. Macari M., Megibow A.J., Balthazar E.J. A pattern approach to the abnormal small bowel: observations at MDCT and CT enterography. Am. J. Roentgenol. 2007, 188:1344-1355.
8. Sousa J.R., Silva A.C., de Paiva A.C., Nunes R.A. Methodology for automatic detection of lung nodules in computerized tomography images. Comput. Methods Programs Biomed. 2010, (98):1-14.
9. Sun T., Wang J., Li X., Lv P., Liu F., Luo Y., Gao Q., Zhu H., Guo X. Comparative evaluation of support vector machines for computer aided diagnosis of lung cancer in CT based on a multi-dimensional data set. Comput. Methods Programs Biomed. 2013, 111:519-524.
10. Kuruvilla J., Gunavathi K. Lung cancer classification using neural networks for CT images. Comput. Methods Programs Biomed. 2014, 113:202-209.
11. Reginelli A., Iacobellis F., Berritto D., Gagliardi G., Di Grezia G., Rossi M., Fonio P., Grassi R. Mesenteric ischemia: the importance of differential diagnosis for the surgeon. BMC Surg. 2013, 13(Suppl. 2):S51. 10.1186/1471-2482-13-S2-S51.
12. Corr P. Pattern Recognition in Diagnostic Imaging 2001, World Health Organization, Geneva.
13. Munro L. Chapter 1: Image Quality Optimization and Control. P. Corr, Pattern Recognition in Diagnostic Imaging 2001, World Health Organization, Geneva.
14. Deng J.D. Improving feature extraction for automatic medical image categorization. Proceedings of 24th International Conference on Image and Vision Computing New Zealand (IVCNZ'09) 2009, 379-384.
15. Pham T.D., Le D.T.P., Xu J., Nguyen D.T., Martindale R.G., Deveney C.W. Personalized identification of abdominal wall hernia meshes on computed tomography. Comput. Methods Programs Biomed. 2014, 113:153-161.
16. Savio A., Garcia-Sebastian M.T., Chyzyk D., Hernandez C., Grana M., Sistiaga A., de Munain A.L., Villanua J. Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI. Comput. Biol. Med. 2011, 41:600-610.
17. Castellano G., Bonilha L., Li L.M., Cendes F. Texture analysis of medical images. Clin. Radiol. 2004, 59:1061-1069.
18. Parekh R. Using texture analysis for medical diagnosis. IEEE MultiMedia 2012, 19:28-37.
19. Gensure R.H., Foran D.J., Lee V.M., Gendel V.M., Jabbour S.K., Carpizo D.R., Nosher J.L., Yang L. Evaluation of hepatic tumor response to Yttrium-90 radioembolization therapy using texture signatures generated from contrast-enhanced CT images. Acad. Radiol. 2012, 19:1201-1207.
20. Wittenberg J., Harisinghani M.G., Jhaveri K., Varghese J.J., Mueller P.R. Algorithmic approach to CT diagnosis of the abnormal bowel wall. RadioGraphics 2002, 22:1093-1109.
21. Jang K.M., Min K., Kim M.J., Koh S.H., Jeon E.Y., Kim I.G., Choi D. Diagnostic performance of CT in the detection of intestinal ischemia associated with small-bowel obstruction using maximal attenuation of region of interest. AJR Am. J. Roentgenol. 2010, 194:957-963.
22. Tuceryan M., Jain A.K. Texture analysis. The Handbook of Pattern Recognition and Computer Vision 1998, 207-248. World Scientific Publishing. 2nd ed. C.H. Chen, L.F. Pau, P.S.P. Wang (Eds.).
23. Sklansky J. Image segmentation and feature extraction. IEEE Trans. Syst. Man Cybern. 1978, 8:237-247.
24. Mariethoz G., Lefebvre S. Bridges between multiple-point geostatistics and texture synthesis: review and guidelines for future research. Comput. Geosci. 2014, 66:66-80.
25. Deutsch C.V., Journel A.G. GSLIB Geostatistical Software Library and User's Guide 1998, Oxford University Press, New York.
26. Isaaks E.H., Srivastava R.M. An Introduction to Applied Geostatistics 1989, Oxford University Press, New York.
27. Matheron G. Principles of geostatistics. Econ. Geol. 1963, 58:1246-1266.
28. De Luca A., Termini S. A definition of a nonprobabilistic entropy in the setting of fuzzy sets theory. Inf. Control 1972, 20:301-312.
29. Zadeh L.A. Similarity relations and fuzzy orderings. Inf. Sci. 1971, 3:177-206.
30. Kosko B. Fuzzy entropy and conditioning. Inf. Sci. 1986, 40:165-174.
31. Caers J. Modeling Uncertainty in the Earth Sciences 2011, Wiley-Blackwell, Oxford.
32. Journel A.G. Combining knowledge from diverse sources: an alternative to traditional data independence hypotheses. Math. Geol. 2002, 34:573-595.
33. Ortiz J.M., Deutsch C.V. Indicator simulation accounting for multiple-point statistics. Math. Geol. 2004, 36:545-565.
34. Otsu N. A threshold selection method from gray-level histogram. IEEE Trans. Syst. Man Cybern. 1979, 9:62-66.
35. Sheedy S.P., Earnest F., Fletcher J.G., Fidler J.L., Hoskin T.L. CT of small-bowel ischemia associated with obstruction in emergency department patients: diagnostic performance evaluation. Radiology 2006, 241:729-736.
36. Tsunoyama T., Pham T.D., Fujita T., Sakamoto T. Automated CT detection of intestinal abnormalities and ischemia for decision making in emergency medicine. BioMed. Eng. Online 2014, 13(Suppl. 1):S3.
37. Pham T.D. Supervised restoration of degraded medical images using multiple-point geostatistics. Comput. Methods Programs Biomed. 2012, 106:201-209.
38. Silva A.C., Carvalho P.C.P., Gattass M. Diagnosis of lung nodule using semivariogram and geometric measures in computerized tomography images. Comput. Methods Programs Biomed. 2005, 79:31-38.
39. Lee Y., Seo J.B., Lee J.G., Kim S.S., Kim N., Kang S.H. Performance testing of several classifiers for differentiating obstructive lung diseases based on texture analysis at high-resolution computerized tomography (HRCT). Comput. Methods Programs Biomed. 2009, 93:206-215.
40. Pham T.D., Yan H. Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms. Proceedings of North America Fuzzy Information Processing Society 1997, 257-262.
41. Pham T.D. Fuzzy posterior-probabilistic fusion. Pattern Recognit. 2011, 44:1023-1030.