Prostate tissue texture feature extraction for suspicious regions identification on TRUS images

Journal of Digital Imaging

Volumn 22, Issue 5, 2009, Pages 503-518

  Mohamed, S S ^a   Li, J ^a   Salama, M M A ^a   Freeman, G ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Biomedical image analysis; Computer aided diagnosis (CAD); Decision support; Image processing

Indexed keywords

ASSISTING TOOLS; BIOMEDICAL IMAGE ANALYSIS; COMPUTER-AIDED DIAGNOSIS (CAD); DATA SETS; DECISION SUPPORT; GABOR FILTER; HIGH FREQUENCY; IMAGE REGIONS; PROOF OF CONCEPT; PROSTATE TISSUE; REGION OF INTEREST; SEGMENTATION METHODS; SPATIAL DOMAINS; TRANSRECTAL ULTRASOUND IMAGES; TRUS IMAGES; WAVELET COEFFICIENTS;

COMPUTER AIDED ANALYSIS; DECISION SUPPORT SYSTEMS; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE SEGMENTATION; IMAGING SYSTEMS; ULTRASONIC IMAGING;

COMPUTER AIDED DIAGNOSIS;

ARTICLE; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ANALYSIS; PRIORITY JOURNAL; PROSTATE; TRANSRECTAL ULTRASONOGRAPHY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; PATTERN RECOGNITION, AUTOMATED; PROSTATE; PROSTATIC NEOPLASMS; RECTUM;

EID: 70349296022     PISSN: 08971889     EISSN: 1618727X     Source Type: Journal    
DOI: 10.1007/s10278-008-9124-1     Document Type: Article

References (14)

1. National Cancer Institute of Canada: Canadian Cancer Statistics 2002. Toronto, Canada, 2002
2. SS Mohamed MMA Salama M Kamel EF El-Sadaany K Rizkalla J Chin 2005 Prostate cancer multi-feature analysis using TRUS images Phys Med Biol 50 15 N175 N185
3. Mohamed SS, Salama MMA: Computer-aided diagnosis for prostate cancer using support vector machine. Publication: Proc SPIE 5744:899-907, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display
4. AC Bovik M Clark WS Geisler 1990 Multichannel texture analysis using localized spatial filters IEEE Trans Pattern Anal Mach Intell 12 1 55 73
5. Bushberg JT, Seibert JA, Leidholdt Jr, EM, Boone JM: The Essential Physics of Medical Imaging, 2nd edition. Philadelphia, Penn: Lippincott, Williams & Wilkins, 2002, pp. 469-553
6. Gonzalez RC, Woods RE: Digital Image Processing, 2nd edition. Upper Saddle River, New Jersey: Prentice Hall, 2002 ch. 7
7. U Scheipers H Ermert H-J Sommerfeld M Garcia-Schurmann T Senge S Philippou 2003 Ultrasounic multifeature tissue characterization for prostate diagnostics Ultrasound Med Biol 29 8 1137 1149
8. RL Galloway Jr KR Cleary A EdsLaine J Fan 1993 Texture classification by wavelet packet signatures IEEE Trans Pattern Anal Mach Intell 15 11 1186 1191
9. B Chiu GH Freeman MMA Salama A Fenster 2004 Prostate segmentation algorithm using dyadic wavelet transform and discrete dynamic contour Phys Med Biol 49 21 4943 4960
10. G Georgiou FS Cohen 2003 Is early detection of liver and breast cancers from ultrasound scans possible? Pattern Recogn Lett 24 729 739
11. D-R Chen R-F Chang W-J Kuo M-C Chen Y-L Huang 2002 Diagnosis of breast tumors with sonographic texture analysis using wavelet transform and neural networks Ultrasound Med Bio 28 10 1301 1310
12. W-L Lee Y-C Chen K-S Hsieh 2003 Ultrasonic liver tissues classification by fractal feature vector based on M-band wavelet transform IEEE Trans Med Imaging 22 3 382 393
13. I Daubechies 1998 Orthonormal basis for compactly supported wavelets Commun Pure Appl Math XLI 909 996
14. DF Gleason 1966 Classification of prostatic carcinomas Cancer Chemother Rep 50 125 128