0000000000516169
AUTHOR
Norashikin Yahya
Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI
In this paper, we present an evaluation of four encoder&ndash
Zonal Segmentation of Prostate T2W-MRI using Atrous Convolutional Neural Network
The number of prostate cancer cases is steadily increasing especially with rising number of ageing population. It is reported that 5-year relative survival rate for man with stage 1 prostate cancer is almost 99% hence, early detection will significantly improve treatment planning and increase survival rate. Magnetic resonance imaging (MRI) technique is a common imaging modality for diagnosis of prostate cancer. MRI provide good visualization of soft tissue and enable better lesion detection and staging of prostate cancer. The main challenge of prostate whole gland segmentation is due to blurry boundary of central gland (CG) and peripheral zone (PZ) which lead to differential diagnosis. Sinc…