Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI
Objectives To develop an automatic method for identification and segmentation of clinically
significant prostate cancer in low-risk patients and to evaluate the performance in a routine …
significant prostate cancer in low-risk patients and to evaluate the performance in a routine …
Collaborative multi-institutional prostate lesion segmentation from MR images using deep federated learning framework
I Shiri, E Showkatian, R Mohammadi… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
To develop a robust and generalizable deep learning (DL) model gathering a massive and
heterogenous dataset is crucial as the DL performances could be varied across different …
heterogenous dataset is crucial as the DL performances could be varied across different …
Boundary-weighted domain adaptive neural network for prostate MR image segmentation
Accurate segmentation of the prostate from magnetic resonance (MR) images provides
useful information for prostate cancer diagnosis and treatment. However, automated …
useful information for prostate cancer diagnosis and treatment. However, automated …
3D APA-Net: 3D adversarial pyramid anisotropic convolutional network for prostate segmentation in MR images
Accurate and reliable segmentation of the prostate gland using magnetic resonance (MR)
imaging has critical importance for the diagnosis and treatment of prostate diseases …
imaging has critical importance for the diagnosis and treatment of prostate diseases …
Active appearance model and deep learning for more accurate prostate segmentation on MRI
Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large
inter-patient prostate shape and texture variability, and lack of a clear prostate boundary …
inter-patient prostate shape and texture variability, and lack of a clear prostate boundary …
[HTML][HTML] Segmentation of the prostate, its zones, anterior fibromuscular stroma, and urethra on the MRIs and multimodality image fusion using U-Net model
SM Rezaeijo, SJ Nesheli, MF Serj… - Quantitative Imaging in …, 2022 - ncbi.nlm.nih.gov
Background Due to the large variability in the prostate gland of different patient groups,
manual segmentation is time-consuming and subject to inter-and intra-reader variations …
manual segmentation is time-consuming and subject to inter-and intra-reader variations …
Encoder-decoder with dense dilated spatial pyramid pooling for prostate MR images segmentation
Automatic segmentation of prostate magnetic resonance (MR) images has great significance
for the diagnosis and clinical application of prostate diseases. It faces enormous challenges …
for the diagnosis and clinical application of prostate diseases. It faces enormous challenges …
CAT-Net: A cross-slice attention transformer model for prostate zonal segmentation in MRI
Prostate cancer is the second leading cause of cancer death among men in the United
States. The diagnosis of prostate MRI often relies on accurate prostate zonal segmentation …
States. The diagnosis of prostate MRI often relies on accurate prostate zonal segmentation …
Automatic high resolution segmentation of the prostate from multi-planar MRI
Individualized and accurate segmentations of the prostate are essential for diagnosis as well
as therapy planning in prostate cancer (PCa). Most of the previously proposed prostate …
as therapy planning in prostate cancer (PCa). Most of the previously proposed prostate …
Prostate segmentation with encoder-decoder densely connected convolutional network (Ed-Densenet)
Prostate cancer is a leading cause of mortality among men. Prostate segmentation of
Magnetic Resonance (MR) images plays a critical role in treatment planning and image …
Magnetic Resonance (MR) images plays a critical role in treatment planning and image …