The added value of a deep learning-based computer-aided detection system on prostate cancer detection among readers with varying level of multiparametric MRI expertise

被引：1
作者：
Yilmaz, Enis C. [1 ]
Turkbey, Baris [1 ]
机构：
[1] NCI, Mol Imaging Branch, NIH, Bethesda, MD USA
来源：
CHINESE CLINICAL ONCOLOGY | 2022年
关键词：
ARTIFICIAL-INTELLIGENCE; DIAGNOSIS;
D O I：
10.21037/cco-22-104
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
引用
收藏
页数：9
相关论文
共 21 条
  • [1] Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway
    Barrett, Tristan
    de Rooij, Maarten
    Giganti, Francesco
    Allen, Clare
    Barentsz, Jelle O.
    Padhani, Anwar R.
    [J]. NATURE REVIEWS UROLOGY, 2023, 20 (01) : 9 - 22
  • [2] Tasks for artificial intelligence in prostate MRI
    Belue, Mason J.
    Turkbey, Baris
    [J]. EUROPEAN RADIOLOGY EXPERIMENTAL, 2022, 6 (01)
  • [3] Comparison of sensitivity and reading time for the use of computer-aided detection (CAD) of pulmonary nodules at MDCT as concurrent or second reader
    F. Beyer
    L. Zierott
    E. M. Fallenberg
    K. U. Juergens
    J. Stoeckel
    W. Heindel
    D. Wormanns
    [J]. European Radiology, 2007, 17 (11) : 2941 - 2947
  • [4] Gaur Sonia, 2018, Oncotarget, V9, P33804, DOI 10.18632/oncotarget.26100
  • [5] Computer-Aided Diagnosis Improves the Detection of Clinically Significant Prostate Cancer on Multiparametric-MRI: A Multi-Observer Performance Study Involving Inexperienced Readers
    Giannini, Valentina
    Mazzetti, Simone
    Cappello, Giovanni
    Doronzio, Valeria Maria
    Vassallo, Lorenzo
    Russo, Filippo
    Giacobbe, Alessandro
    Muto, Giovanni
    Regge, Daniele
    [J]. DIAGNOSTICS, 2021, 11 (06)
  • [6] Multiparametric magnetic resonance imaging of the prostate with computer-aided detection: experienced observer performance study
    Giannini, Valentina
    Mazzetti, Simone
    Armando, Enrico
    Carabalona, Silvia
    Russo, Filippo
    Giacobbe, Alessandro
    Muto, Giovanni
    Regge, Daniele
    [J]. EUROPEAN RADIOLOGY, 2017, 27 (10) : 4200 - 4208
  • [7] Prostate Imaging Quality (PI-QUAL): A New Quality Control Scoring System for Multiparametric Magnetic Resonance Imaging of the Prostate from the PRECISION trial
    Giganti, Francesco
    Allen, Clare
    Emberton, Mark
    Moore, Caroline M.
    Kasivisvanathan, Veeru
    [J]. EUROPEAN UROLOGY ONCOLOGY, 2020, 3 (05): : 615 - 619
  • [8] Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study
    Greer, Matthew D.
    Lay, Nathan
    Shih, Joanna H.
    Barrett, Tristan
    Bittencourt, Leonardo Kayat
    Borofsky, Samuel
    Kabakus, Ismail
    Law, Yan Mee
    Marko, Jamie
    Shebel, Haytham
    Mertan, Francesca V.
    Merino, Maria J.
    Wood, Bradford J.
    Pinto, Peter A.
    Summers, Ronald M.
    Choyke, Peter L.
    Turkbey, Baris
    [J]. EUROPEAN RADIOLOGY, 2018, 28 (10) : 4407 - 4417
  • [9] Prostate Cancer: Computer-aided Diagnosis with Multiparametric 3-T MR Imaging-Effect on Observer Performance
    Hambrock, Thomas
    Vos, Pieter C.
    Hulsbergen-van de Kaa, Christina A.
    Barentsz, Jelle O.
    Huisman, Henkjan J.
    [J]. RADIOLOGY, 2013, 266 (02) : 521 - 530
  • [10] Deep learning-assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge
    Hosseinzadeh, Matin
    Saha, Anindo
    Brand, Patrick
    Slootweg, Ilse
    de Rooij, Maarten
    Huisman, Henkjan
    [J]. EUROPEAN RADIOLOGY, 2022, 32 (04) : 2224 - 2234
123