Prostate segmentation: an efficient convex optimization approach with axial symmetry using 3-D TRUS and MR images.
We propose a novel global optimization-based approach to segmentation of 3-D prostate transrectal ultrasound (TRUS) and T2 weighted magnetic resonance (MR) images, enforcing inherent axial symmetry of prostate shapes to simultaneously adjust a series of 2-D slice-wise segmentations in a "global" 3-D sense. We show that the introduced challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. In this regard, we propose a novel coherent continuous max-flow model (CCMFM), which derives a new and efficient duality-based algorithm, leading to a GPU-based implementation to achieve high computational speeds. Experiments with 25 3-D TRUS images and 30 3-D T2w MR images from our dataset, and 50 3-D T2w MR images from a public dataset, demonstrate that the proposed approach can segment a 3-D prostate TRUS/MR image within 5-6 s including 4-5 s for initialization, yielding a mean Dice similarity coefficient of 93.2%±2.0% for 3-D TRUS images and 88.5%±3.5% for 3-D MR images. The proposed method also yields relatively low intra- and inter-observer variability introduced by user manual initialization, suggesting a high reproducibility, independent of observers.
Wu
W
Qiu
Jing
J
Yuan
Eranga
E
Ukwatta
Yue
Y
Sun
Martin
M
Rajchl
Aaron
A
Fenster
D000465:Algorithms; D000704:Analysis of Variance; D016208:Databases, Factual; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D011467:Prostate / Q000000981:diagnostic imaging* / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D015203:Reproducibility of Results; D014463:Ultrasonography