[HTML][HTML] What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?
The present study aimed to explore the potential of artificial intelligence (AI) methodology
based on magnetic resonance (MR) images to aid in the management of prostate cancer …
based on magnetic resonance (MR) images to aid in the management of prostate cancer …
Diagnostic performance of prostate-specific antigen density for detecting clinically significant prostate cancer in the era of magnetic resonance imaging: a systematic …
S Wang, J Kozarek, R Russell, M Drescher… - European Urology …, 2024 - Elsevier
Context There has been a dramatic increase in the use of prostate magnetic resonance
imaging (MRI) in the diagnostic workup. With prostate volume calculated from MRI, prostate …
imaging (MRI) in the diagnostic workup. With prostate volume calculated from MRI, prostate …
Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer
Objective To identify which patient with prostate cancer (PCa) could safely avoid extended
pelvic lymph node dissection (ePLND) by predicting lymph node invasion (LNI), via a …
pelvic lymph node dissection (ePLND) by predicting lymph node invasion (LNI), via a …
[HTML][HTML] Machine learning-based models enhance the prediction of prostate cancer
S Chen, T Jian, C Chi, Y Liang, X Liang, Y Yu… - Frontiers in …, 2022 - frontiersin.org
Purpose PSA is currently the most commonly used screening indicator for prostate cancer.
However, it has limited specificity for the diagnosis of prostate cancer. We aim to construct …
However, it has limited specificity for the diagnosis of prostate cancer. We aim to construct …
iPCa-Net: A CNN-based framework for predicting incidental prostate cancer using multiparametric MRI
L Wen, S Wang, X Pan, Y Liu - Computerized Medical Imaging and …, 2023 - Elsevier
Incidental prostate cancer (iPCa) is an early stage of clinically significant prostate cancer
(csPCa) and is typically asymptomatic, making it difficult to detect in clinical practice. The …
(csPCa) and is typically asymptomatic, making it difficult to detect in clinical practice. The …
[HTML][HTML] AtPCa-Net: anatomical-aware prostate cancer detection network on multi-parametric MRI
Multi-parametric MRI (mpMRI) is widely used for prostate cancer (PCa) diagnosis. Deep
learning models show good performance in detecting PCa on mpMRI, but domain-specific …
learning models show good performance in detecting PCa on mpMRI, but domain-specific …
AI-powered radiomics: revolutionizing detection of urologic malignancies
DG Gelikman, S Rais-Bahrami, PA Pinto… - Current Opinion in …, 2024 - journals.lww.com
Radiomics integrated with artificial intelligence offers a pioneering approach to urologic
oncology, ushering in an era of enhanced diagnostic precision and reduced invasiveness …
oncology, ushering in an era of enhanced diagnostic precision and reduced invasiveness …
[HTML][HTML] MRI T2w Radiomics-Based Machine Learning Models in Imaging Simulated Biopsy Add Diagnostic Value to PI-RADS in Predicting Prostate Cancer: A …
JC Liu, XH Ruan, TT Chun, C Yao, D Huang… - …, 2024 - pmc.ncbi.nlm.nih.gov
Simple Summary Prostate mpMRI is currently the most widely used image diagnosis
approach to detect prostate cancer, while the PI-RADS system was developed to …
approach to detect prostate cancer, while the PI-RADS system was developed to …
Comparison of intensity normalization methods in prostate, brain, and breast cancer multi-parametric magnetic resonance imaging
SR Duenweg, SA Bobholz, AK Lowman, A Winiarz… - 2024 - researchsquare.com
Intensity variation in multi-parametric magnetic resonance imaging (MP-MRI) poses
challenges for MRI analyses. Previous studies have employed several normalization …
challenges for MRI analyses. Previous studies have employed several normalization …
[引用][C] Multiparametrik prostat manyetik rezonans görüntülemenin uzun dönem takip sonuçları ve negatif prediktif değeri
Ö Önder - 2022 - Tıp Fakültesi