Semi automatic MRI prostate segmentation based on wavelet multiscale products.
Currently, prostate cancer is the third leading cause of cancer-related deaths among men in North America. As with many others types of cancer, early detection and treatment greatly increases the patient's chance of survival. MRI prostate segmentation allows clinical personnel to design an accurate treatment plan. A novel method for MRI prostate imagery segmentation is proposed in this paper. This method exploits the different behavior presented by signal singularities and noise in the wavelet domain in order to accurately detect the borders around the prostate. The prostate contour is then traced by using a set of spatially variant rules that are based on prior knowledge about the general shape of the prostate. The proposed method yielded promising results when applied to real data.
Flores-Tapia
Daniel
D
Department of Electrical and Computer Engineering, University of Manitoba, Manitoba, Canada. dflores@ee.umanitoba.ca
Thomas
Gabriel
G
Venugopal
Niranjan
N
McCurdy
Boyd
B
Pistorius
Stephen
S
D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008495:Medical Oncology / Q000379:methods; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D011467:Prostate / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000532:radiotherapy*; D011871:Radiology / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity