Challenge of prostate MRI segmentation on T2-weighted images: inter-observer variability and impact of prostate morphology

被引:0
|
作者
Sarah Montagne
Dimitri Hamzaoui
Alexandre Allera
Malek Ezziane
Anna Luzurier
Raphaelle Quint
Mehdi Kalai
Nicholas Ayache
Hervé Delingette
Raphaële Renard-Penna
机构
[1] Assistance Publique des Hôpitaux de Paris,Academic Department of Radiology, Hôpital Pitié
[2] Assistance Publique des Hôpitaux de Paris,Salpétrière
[3] Université Côte D’Azur,Academic Department of Radiology, Hôpital Tenon
[4] Sorbonne Universités,Inria, Epione Team
来源
关键词
Prostate; MRI; Segmentation; Zones; Atlas;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [31] The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images
    Sunoqrot, Mohammed R. S.
    Selnaes, Kirsten M.
    Sandsmark, Elise
    Langorgen, Sverre
    Bertilsson, Helena
    Bathen, Tone F.
    Elschot, Mattijs
    DIAGNOSTICS, 2021, 11 (09)
  • [32] Effect of Echo Times on Prostate Cancer Detection on T2-Weighted Images
    Chatterjee, Aritrick
    Nolan, Paul
    Sun, Chongpeng
    Mathew, Melvy
    Dwivedi, Durgesh
    Yousuf, Ambereen
    Antic, Tatjana
    Karczmar, Gregory S.
    Oto, Aytekin
    ACADEMIC RADIOLOGY, 2020, 27 (11) : 1555 - 1563
  • [33] Performance and inter-observer variability of prostate MRI (PI-RADS version 2) outside high-volume centres
    Kohestani, Kimia
    Wallstrom, Jonas
    Dehlfors, Niclas
    Sponga, Ole Martin
    Mansson, Marianne
    Josefsson, Andreas
    Carlsson, Sigrid
    Hellstrom, Mikael
    Hugosson, Jonas
    SCANDINAVIAN JOURNAL OF UROLOGY, 2019, 53 (05) : 304 - 311
  • [34] T2-weighted MRI of the prostate after IMRT - Signal changes and role of morphologic MRI in the posttherapeutic management of prostate cancer
    Thieke, C.
    Aftab, K.
    Giesel, F.
    Zamecnik, P.
    Kauczor, H.
    Huber, P. E.
    Debus, J.
    Delorme, S.
    Zechmann, C. M.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2008, 72 (01): : S320 - S321
  • [35] Inter-observer variability for the six rigid-body setup parameters in prostate treatments
    Boswell, S
    Keller, H
    Mackie, TR
    Ruchala, K
    MEDICAL PHYSICS, 2002, 29 (06) : 1310 - 1310
  • [36] 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
  • [37] Inter-observer variability in OAR and target volume delineation in curative prostate cancer patients
    Tiigi, K.
    Tiigi, R.
    Oro, I.
    Adamson, M.
    Kolk, K.
    Poldveer, M.
    RADIOTHERAPY AND ONCOLOGY, 2018, 127
  • [38] Incidental Findings of Abnormal Prostate T2-Weighted Signal in Pelvic MRI Examinations
    Oliveira, G.
    Haker, S.
    Tempany, C.
    Mulkern, R.
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2009, 192 (05)
  • [39] The Potential for Deep Learning Reconstruction to Improve the Quality of T2-weighted Prostate MRI
    Turkbey, Baris
    RADIOLOGY, 2023, 308 (03)
  • [40] Combining T2-weighted with dynamic MR images for computerized classification of prostate lesions
    Vos, Pieter C.
    Hambrock, Thomas
    Barentsz, Jelle O.
    Huisman, Henkjan J.
    MEDICAL IMAGING 2008: COMPUTER-AIDED DIAGNOSIS, PTS 1 AND 2, 2008, 6915