Quantitative assessment of pap smear cells by PC-based cytopathologic image analysis system and support vector machine

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4901 LNCS, Issue , 2008, Pages 192-199

  Huang, Po Chi ^a   Chan, Yung Kuan ^b   Chan, Po Chou ^c   Chen, Yung Fu ^d   Chen, Rung Ching ^e   Huang, Yu Ruei ^e  

^a TAICHUNG HOSPITAL   (Taiwan)

^b NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

^c CENTRAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^d CHINA MEDICAL UNIVERSITY   (Taiwan)

^e CHAOYANG UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

CELLULAR CLASSIFICATION; CELLULAR IMAGES; CYTOLOGIC SCREENING; MORPHOMETRIC PARAMETERS;

CELLS; CLASSIFICATION (OF INFORMATION); IMAGE ANALYSIS; PARAMETER ESTIMATION; PATHOLOGY; SUPPORT VECTOR MACHINES;

CYTOLOGY;

EID: 38549176974     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (17)

1. DeMay, R.M.: Common problems in Papanicolaou smear interpretation. Arch. Pathol. Lab. Med. 121, 229-238 (1997)
2. Hartmann, K.E., Nanda, K., Hall, S., Myers, E.: Technologie advances for evaluation of cervical cytology: is newer better? Obstet. Gynecol. Surv. 56, 765-774 (2001)
3. Stoler, M.H.: Advances in cervical screening technology. Mod. Pathol. 13, 275-284 (2000)
4. Dawson, A.E.: Can we change the way we screen? the ThinPrep Imaging System. Cancer 102, 340-344 (2004)
5. Kardos, T.F.: The FocalPoint System: FocalPoint slide profiler and FocalPoint GS. Cancer 102, 334-339 (2004)
6. Mango, L.J.: Reducing false negatives in clinical practice: the role of neural network technology. Am. J. Obstet. Gynecol. 175, 1114-1119 (1996)
7. Taylor, R.N., Gagnon, M., Lange, J., Lee, T., Draut, R., Kujawski, E.: CytoView. A prototype computer image-based Papanicolaou smear proficiency test. Acta. Cytol. 43, 1045-1051 (1999)
8. Doornewaard, H., van der Schouw, Y.T., van der Graaf, Y., Bos, A.B., van den Tweel, J.G.: Observer variation in cytologic grading for cervical dysplasia of Papanicolaou smears with the PAPNET testing system. Cancer 87, 178-183 (1999)
9. Harris, M.V., Cason, Z., Benghuzzi. H., Tucci, M.: Cytomorphological assessment of benign and malignant dense hyperchromatic groups in cervicovaginal smears. Biomed. Sci. Instrum. 36, 349-354 (2000)
10. Nunobiki, O., Sato, M., Taniguchi, E., Tang, W., Nakamura, M., Utsunomiya, H., Nakamura, Y., Mori, I., Kakudo, K.: Color image analysis of cervical neoplasia using RGB computer color specification. Anal. Quant. Cytol. Histol. 24, 289-294 (2002)
11. Arora, B., Setia, S., Rekhi, B.: Role of computerized morphometric analysis in diagnosis of effusion specimens. Diagn. Cytopathol. 34, 670-675 (2006)
12. Wang, S.L., Wu, M.T., Yang, S.F., Chan, H.M., Chai, C.Y.: Computerized nuclear morphometry in thyroid follicular neoplasms. Pathol. Int. 55, 703-706 (2005)
13. Murata, S., Mochizuki, K., Nakazawa, T., Kondo, T., Nakamura, N., Yamashita, H., Urata, Y., Ashihara, T., Katoh, R.: Morphological abstraction of thyroid tumor cell nuclei using morphometry with factor analysis. Microsc. Res. Tech. 61, 457-462 (2003)
14. Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. Software (2001), available at http://www.csie.ntu.edu.tw/cjlin/libsvm
15. Naib, Z.M.: Cytopathology, 4th edn., pp. 65-67. Little, Brown and Company, Bosten, New York (1996)
16. Ramesh, B.V., Padaki, V.C., Hegde, K.S., Hazarika, D., Verghese, C.A.: An interactive image analysis system for quantitative cytology & to classify cervical cells. Indian J. Med. Res. 96, 338-343 (1992)
17. Kirillov, V., Stebenyaeva, E., Paplevka, A., Demidchik, E.: A rapid method for diagnosing regional metastases of papillary thyroid cancer with morphometry. Microsc. Res. Tech 69, 721-728 (2006)