Deep learning for real-time, automatic, and scanner-adapted prostate (zone) segmentation of transrectal ultrasound, for example, magnetic resonance imaging …
RJG van Sloun, RR Wildeboer, CK Mannaerts… - European urology …, 2021 - Elsevier
Background Although recent advances in multiparametric magnetic resonance imaging
(MRI) led to an increase in MRI-transrectal ultrasound (TRUS) fusion prostate biopsies …
(MRI) led to an increase in MRI-transrectal ultrasound (TRUS) fusion prostate biopsies …
[HTML][HTML] External validation of a convolutional neural network for the automatic segmentation of intraprostatic tumor lesions on 68Ga-PSMA PET images
S Ghezzo, S Mongardi, C Bezzi… - Frontiers in …, 2023 - frontiersin.org
Introduction State of the art artificial intelligence (AI) models have the potential to become a
“one-stop shop” to improve diagnosis and prognosis in several oncological settings. The …
“one-stop shop” to improve diagnosis and prognosis in several oncological settings. The …
Automatic segmentation of prostate MRI based on 3D pyramid pooling Unet
Y Li, C Lin, Y Zhang, S Feng, M Huang, Z Bai - Medical Physics, 2023 - Wiley Online Library
Purpose Automatic segmentation of prostate magnetic resonance (MR) images is crucial for
the diagnosis, evaluation, and prognosis of prostate diseases (including prostate cancer). In …
the diagnosis, evaluation, and prognosis of prostate diseases (including prostate cancer). In …
[HTML][HTML] Prostate MRI: what to consider when shopping for AI tools
T Penzkofer - European Radiology, 2024 - Springer
For at least 40 years, there has been hope that prostate cancer could automatically be
diagnosed on imaging. Technologies were initially researched on ultrasound images [1], but …
diagnosed on imaging. Technologies were initially researched on ultrasound images [1], but …
Computer aided diagnosis of clinically significant prostate cancer in low-risk patients on multi-parametric MR images using deep learning
The purpose of this study was to develop a quantitative method for detection and
segmentation of clinically significant (ISUP grade≥ 2) prostate cancer (PCa) in low-risk …
segmentation of clinically significant (ISUP grade≥ 2) prostate cancer (PCa) in low-risk …
Deep convolutional encoder-decoders for prostate cancer detection and classification
Prostate cancer accounts for approximately 11% of all cancer cases. Definitive diagnosis is
made by histopathological examination of tissue biopsies. Recently, there have been strong …
made by histopathological examination of tissue biopsies. Recently, there have been strong …
Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections
Accurate and automated prostate whole gland and central gland segmentations on MR
images are essential for aiding any prostate cancer diagnosis system. Our work presents a 2 …
images are essential for aiding any prostate cancer diagnosis system. Our work presents a 2 …
[HTML][HTML] Investigation and benchmarking of U-Nets on prostate segmentation tasks
In healthcare, a growing number of physicians and support staff are striving to facilitate
personalized radiotherapy regimens for patients with prostate cancer. This is because …
personalized radiotherapy regimens for patients with prostate cancer. This is because …
Classification of clinical significance of MRI prostate findings using 3D convolutional neural networks
Prostate cancer (PCa) remains a leading cause of cancer mortality among American men.
Multi-parametric magnetic resonance imaging (mpMRI) is widely used to assist with …
Multi-parametric magnetic resonance imaging (mpMRI) is widely used to assist with …
Automatic prostate segmentation on MR images with deep network and graph model
Automated prostate diagnoses and treatments have gained much attention due to the high
mortality rate of prostate cancer. In particular, unsupervised (automatic) prostate …
mortality rate of prostate cancer. In particular, unsupervised (automatic) prostate …