Acharya, U.R. and Molinari, F. and Sree, S.V. and Swapna, G. and Saba, L. and Guerriero, S. and Suri, J.S. (2015) Ovarian tissue characterization in ultrasound: A Review. Technology in Cancer Research & Treatment, 14 (3). pp. 251-261. ISSN 1533-0338, DOI https://doi.org/10.1177/1533034614547445.
Full text not available from this repository.
Official URL: http://www.ncbi.nlm.nih.gov/pubmed/25230716
Abstract
Ovarian cancer is the most common cause of death among gynecological malignancies. We discuss different types of clinical and nonclinical features that are used to study and analyze the differences between benign and malignant ovarian tumors. Computer-aided diagnostic (CAD) systems of high accuracy are being developed as an initial test for ovarian tumor classification instead of biopsy, which is the current gold standard diagnostic test. We also discuss different aspects of developing a reliable CAD system for the automated classification of ovarian cancer into benign and malignant types. A brief description of the commonly used classifiers in ultrasound-based CAD systems is also given.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | ISI Document Delivery No.: CJ1VL Times Cited: 0 Cited Reference Count: 57 Cited References: Acharya UR, 2013, J DIGIT IMAGING, V26, P544, DOI 10.1007/s10278-012-9553-8 Acharya UR, 2012, TECHNOL CANCER RES T, V11, P543, DOI 10.7785/tcrt.2012.500272 Acharya UR, 2014, TECHNOL CANCER RES T, V13, P529, DOI 10.7785/tcrtexpress.2013.600273 Acharya UR, 2014, ULTRASCHALL MED, V35, P237, DOI 10.1055/s-0032-1330336 Assareh A, 2007, IEEE S COMP INT BIOI, P502 Bankhead CR, 2005, BJOG-INT J OBSTET GY, V112, P857, DOI 10.1111/j.1471-0528.2005.00572.x Bast RC, 2005, INT J GYNECOL CANCER, V15, P274, DOI 10.1111/j.1525-1438.2005.00441.x Biagiotti R, 1999, RADIOLOGY, V210, P399 BOURNE TH, 1994, GYNECOL ONCOL, V52, P379, DOI 10.1006/gyno.1994.1065 Bruning J, 1997, METHOD INFORM MED, V36, P201 Burges C., 1998, DATA MIN KNOWL DISC, V2, P1, DOI DOI 10.1023/A:1009715923555 Christianini N., 2000, SUPPORT VECTOR MACHI Chua K. C., 2009, Journal of Medical Engineering & Technology, V33, P42, DOI 10.1080/03091900701559408 Foulkes WD, 2013, J PATHOL, V230, P347, DOI 10.1002/path.4205 Goff BA, 2004, JAMA-J AM MED ASSOC, V291, P2705, DOI 10.1001/jama.291.22.2705 GUPTA R, 1995, PHYS MED BIOL, V40, P835, DOI 10.1088/0031-9155/40/5/009 Han J., 2006, DATA MINING CONCEPTS Haubrich RA, 1985, J GEOPHYS RES, P1415 Haykin S. O., 2008, NEURAL NETWORKS LEAR Horner M. J., 2009, SEER CANC STAT REV 1 Hsu C.W., 2003, TECHNICAL REPORT HU M, 1962, IRE T INFORM THEOR, V8, P179 Jemal A, 2010, CA-CANCER J CLIN, V60, P277, DOI 10.3322/caac.20073, 10.1002/caac.20073 Kocioek M, 2001, P INT C SIGN EL SYST, P163 Krishnan M. M. R., 2012, KNOWL-BASED SYST, V33, P73, DOI DOI 10.1016/J.KNOSYS.2012.02.010 Lakhani SR, 2004, CLIN CANCER RES, V10, P2473, DOI 10.1158/1078-0432.CCR-1029-3 Laura J, 2010, WALL ST J Laws K. I., 1980, SPIE IMAGE PROCESSIN, V0238, P376 Lenic M, 2007, COMP MED SY, P205, DOI 10.1109/CBMS.2007.97 Liao S, 2009, IEEE T IMAGE PROCESS, V18, P1107, DOI 10.1109/TIP.2009.2015682 Lucidarme O, 2010, EUR RADIOL, V20, P1822, DOI 10.1007/s00330-010-1750-6 Meng H, 2008, BIOMEDICAL ENG, P668 Muller KR, 2001, IEEE T NEURAL NETWOR, V12, P181, DOI 10.1109/72.914517 Nikias CL, 1993, IEEE SIGNAL PROC MAG, V10, P10, DOI 10.1109/79.221324 NIKIAS CL, 1987, P IEEE, V75, P869, DOI 10.1109/PROC.1987.13824 Ojala T, 2002, IEEE T PATTERN ANAL, V24, P971, DOI 10.1109/TPAMI.2002.1017623 Ojala T, 1996, PATTERN RECOGN, V29, P51, DOI 10.1016/0031-3203(95)00067-4 Petricoin EF, 2002, LANCET, V359, P572, DOI 10.1016/S0140-6736(02)07746-2 Pharwaha APS, 2009, LECT NOTES ENG COMPU, V2179 Piek JMJ, 2008, ADV EXP MED BIOL, V622, P79, DOI 10.1007/978-0-387-68969-2_7 Rao KA, 2008, TXB GYNAECOLOGY Renz C, 2002, NEURAL INFORM PROCES, V2, P809 Rossing MA, 2010, J NATL CANCER I, V102, P222, DOI 10.1093/jnci/djp500 Ryerson AB, 2007, OBSTET GYNECOL, V109, P1053, DOI 10.1097/01.AOG.0000260392.70365.5e SASSONE AM, 1991, OBSTET GYNECOL, V78, P70 Sohail AM, 2010, I S BIOMED IMAGING, P288, DOI 10.1109/ISBI.2010.5490352 Sohail ASM, 2011, I S BIOMED IMAGING, P10, DOI 10.1109/ISBI.2011.5872343 Sparkman DO, 2000, MASS SPECTROMETRY DE Tailor A, 1999, BRIT J OBSTET GYNAEC, V106, P21, DOI 10.1111/j.1471-0528.1999.tb08080.x Tan TZ, 2008, ARTIF INTELL MED, V43, P207, DOI 10.1016/j.artmed.2008.04.003 Tang KL, 2010, BMC BIOINFORMATICS, V11, DOI 10.1186/1471-2105-11-109 Vapnik V., 1998, STAT LEARNING THEORY Vlahos NF, 2010, BEST PRACT RES CL OB, V24, P39, DOI 10.1016/j.bpobgyn.2009.08.004 Wasserman PD, 1993, ADV METHODS NEURAL C Zaidi S, 2007, INT J GYNECOL OBSTET, V99, P195, DOI 10.1016/j.ijgo.2007.08.002 Zhang BC, 2010, IEEE T IMAGE PROCESS, V19, P533, DOI 10.1109/TIP.2009.2035882 Zimmer Y, 2003, ULTRASOUND MED BIOL, V29, P1561, DOI 10.1016/j.ultrasmedbio.2003.08.013 Acharya, U. Rajendra Molinari, Filippo Sree, S. Vinitha Swapna, G. Saba, Luca Guerriero, Stefano Suri, Jasjit S. Engineering, Faculty /I-7935-2015; Guerriero, Stefano/ Engineering, Faculty /0000-0002-4848-7052; Guerriero, Stefano/0000-0002-1359-7155 0 SAGE PUBLICATIONS INC THOUSAND OAKS TECHNOL CANCER RES T |
| Uncontrolled Keywords: | Ovarian, tumor, malignant, classifier, feature, benign, texture, LOCAL BINARY PATTERNS, HIGHER-ORDER SPECTRA, TEXTURE CLASSIFICATION, TUMOR CHARACTERIZATION, ONLINE PARADIGM, NEURAL-NETWORKS, CANCER, MALIGNANCY, SYMPTOMS, DIAGNOSIS, |
| Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering |
| Depositing User: | Mr Jenal S |
| Date Deposited: | 08 Apr 2016 02:28 |
| Last Modified: | 08 Apr 2016 02:28 |
| URI: | http://eprints.um.edu.my/id/eprint/15748 |
Actions (login required)
 |
View Item |
