PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI (vol 129, pg 901, 2024)

被引：0

作者：

Laudicella, Riccardo ^{[1
,2
,3
]}

Comelli, Albert ^{[3
]}

Schwyzer, Moritz ^{[4
]}

Stefano, Alessandro ^{[5
]}

Konukoglu, Ender ^{[6
]}

Messerli, Michael ^{[1
]}

Baldari, Sergio ^{[2
]}

Eberli, Daniel ^{[7
]}

Burger, Irene A. ^{[1
,8
]}

机构：

[1] Univ Zurich, Univ Hosp Zurich, Dept Nucl Med, Zurich, Switzerland

[2] Univ Messina, Dept Biomed & Dent Sci & Morpho Funct Imaging, Nucl Med Unit, Messina, Italy

[3] Ri MED Fdn, Palermo, Italy

[4] Univ Hosp Zurich, Inst Diagnost & Intervent Radiol, Zurich, Switzerland

[5] Natl Res Council IBFM CNR, Inst Mol Bioimaging & Physiol, Cefalu, Italy

[6] Swiss Fed Inst Technol, Comp Vis Lab, Zurich, Switzerland

[7] Univ Hosp Zurich, Dept Urol, Zurich, Switzerland

[8] Cantonal Hosp Baden, Dept Nucl Med, Baden, Switzerland

来源：

RADIOLOGIA MEDICA | 2024年 / 129卷 / 09期

关键词：

D O I：

10.1007/s11547-024-01829-4

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

引用

页码：1428 / 1428

页数：1

共 50 条

[21] Prediction of pituitary adenoma surgical consistency: radiomic data mining and machine learning on T2-weighted MRI
Renato Cuocolo
Lorenzo Ugga
Domenico Solari
Sergio Corvino
Alessandra D’Amico
Daniela Russo
Paolo Cappabianca
Luigi Maria Cavallo
Andrea Elefante
Neuroradiology, 2020, 62 : 1649 - 1656
[22] Usefulness of T2-Weighted Images with Deep-Learning-Based Reconstruction in Nasal Cartilage
Gao, Yufan
Liu, Weiyin
Li, Liang
Liu, Changsheng
Zha, Yunfei
DIAGNOSTICS, 2023, 13 (19)
[23] Accelerated 3D high-resolution T2-weighted breast MRI with deep learning constrained compressed sensing, comparison with conventional T2-weighted sequence on 3.0 T
Yang, Fan
Pan, Xuelin
Zhu, Ke
Xiao, Yitian
Yue, Xun
Peng, Pengfei
Zhang, Xiaoyong
Huang, Juan
Chen, Jie
Yuan, Yuan
Sun, Jiayu
EUROPEAN JOURNAL OF RADIOLOGY, 2022, 156
[24] Verification of image quality improvement by deep learning reconstruction to 1.5 T MRI in T2-weighted images of the prostate gland
Sato, Yoshiomi
Ohkuma, Kiyoshi
RADIOLOGICAL PHYSICS AND TECHNOLOGY, 2024, 17 (03) : 756 - 764
[25] Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning
Wang, Liang
Zhang, Peipei
Feng, Yanhui
Lv, Wenzhi
Min, Xiangde
Liu, Zhiyong
Li, Jin
Feng, Zhaoyan
BMC CANCER, 2025, 25 (01)
[26] Prediction of microvascular invasion in hepatocellular carcinoma patients with MRI radiomics based on susceptibility weighted imaging and T2-weighted imaging
Geng, Zhijun
Wang, Shutong
Ma, Lidi
Zhang, Cheng
Guan, Zeyu
Zhang, Yunfei
Yin, Shaohan
Lian, Shanshan
Xie, Chuanmiao
RADIOLOGIA MEDICA, 2024, 129 (08): : 1130 - 1142
[27] Editorial for "Comparison of a Deep Learning-Accelerated Versus Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate"
Wu, Zhe
Bhayana, Rajesh
Uludag, Kamil
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2023, 58 (04) : 1065 - 1066
[28] Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI
Bischoff, Leon M.
Peeters, Johannes M.
Weinhold, Leonie
Krausewitz, Philipp
Ellinger, Joerg
Katemann, Christoph
Isaak, Alexander
Weber, Oliver M.
Kuetting, Daniel
Attenberger, Ulrike
Pieper, Claus C.
Sprinkart, Alois M.
Luetkens, Julian A.
RADIOLOGY, 2023, 308 (03)
[29] Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate
Tong, Angela
Bagga, Barun
Petrocelli, Robert
Smereka, Paul
Vij, Abhinav
Qian, Kun
Grimm, Robert
Kamen, Ali
Keerthivasan, Mahesh B.
Nickel, Marcel Dominik
von Busch, Heinrich
Chandarana, Hersh
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2023, 58 (04) : 1055 - 1064
[30] Deep phenotyping the cervical spine: automatic characterization of cervical degenerative phenotypes based on T2-weighted MRI
Frank Niemeyer
Fabio Galbusera
Youping Tao
Frank M. Phillips
Howard S. An
Philip K. Louie
Dino Samartzis
Hans-Joachim Wilke
European Spine Journal, 2023, 32 : 3846 - 3856

← 1 2 3 4 5 →