Journal of Optoelectronics · Laser, Volume. 34, Issue 12, 1337(2023)

Prostate magnetic resonance image segmentation based on improved 3D UNet

SANG Zijiang1, SHAO Yeqin2、*, and XU Changyan1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    References(17)

    [1] [1] CULP M B,SOERJOMATARAM I,EFSTATHIOU J A,et al.Recent global patterns in prostate cancer incidence and mortality rates[J].European Urology,2020,77(1):38-52.

    [2] [2] SHELHAMER E,LONG J,DARRELL T.Fully convolutional networks for semantic segmentation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,39(4):640-651.

    [3] [3] RONNEBERGER O,FISCHER P,BROX T.U-Net:Convolutional networks for biomedical image segmentation[C]//Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015,October 5-9,2015,Munich,Germany.Berlin:Springer,2015:234-241.

    [4] [4] BAI H,LU C,MA M,et al.An improved U-Net for cell confluence estimation[J].Optoelectronics Letters,2022,18(6):378-384.

    [5] [5] ZHOU W,TAO X,WEI Z,et al.Automatic segmentation of 3D prostate MR images with iterative localization refinement[J].Digital Signal Processing,2020,98:102649.

    [6] [6] IEK ,ABDULKADIR A,LIENKAMP S S,et al.3D U-Net:Learning dense volumetric segmentation from sparse annotation[C]//Medical Image Computing and Computer-Assisted Intervention,October 17-21,2016,Athens,Greece.Berlin:Springer,2016:424-432.

    [7] [7] MILLETARI F,NAVAB N,AHMADI S A.V-Net:Fully convolutional neural networks for volumetric medical image segmentation[C]//2016 Fourth International Conference on 3D Vision (3DV),October 25-28,2016,Stanford,CA,USA.New York:IEEE,2016:565-571.

    [8] [8] ZHU Q,DU B,YAN P.Boundary-weighted domain adaptive neural network for prostate MR image segmentation[J].IEEE Transactions on Medical Imaging,2020,39(3):753-763.

    [9] [9] JIA H,CAI W,HUANG H,et al.Learning multi-scale synergic discriminative features for prostate image segmentation[J].Pattern Recognition,2022,126:108556.

    [10] [10] JIA H,SONG Y,HUANG H,et al.HD-Net:hybrid discriminative network for prostate segmentation in MR images[C]//Medical Image Computing and Computer Assisted Intervention-MICCAI 2019,October 13-17,2019,Shenzhen,China.Berlin:Springer,2019:110-118.

    [12] [12] DAI Y,GIESEKE F,OEHMCKE S,et al.Attentional feature fusion[C]//IEEE/CVF Winter Conference on Applications of Computer Vision,January 3-8,2021,Waikoloa,HI,USA.New York:IEEE,2021:3560-3569.

    [13] [13] ISENSEE F,JAEGER P F,KOHL S A A,et al.nnU-Net:a self-configuring method for deep learning-based biomedical image segmentation[J].Nature Methods,2021,18(2):203-211.

    [14] [14] HU J,SHEN L,SUN G.Squeeze-and-excitation networks[C]//IEEE Conference on Computer Vision and Pattern Recognition,June 18-23,2018,Salt Lake City,UT,USA.New York:IEEE,2018:7132-7141.

    [15] [15] TOMAR N K,JHA D,BAGCI U,et al.TGANet:Text-guided attention for improved polyp segmentation[C]//Medical Image Computing and Computer Assisted Intervention-MICCAI 2022, September 18-22, 2022,Singapore.Cham:Springer, 2022:151-160.

    [16] [16] HUANG G,LIU Z,VAN DER MAATEN L,et al.Densely connected convolutional networks[C]//IEEE Conference on Computer Vision and Pattern Recognition,July 21-26,2017,Honolulu,HI,USA.New York:IEEE,2017:4700-4708.

    [17] [17] TAGHANAKI S A,ZHENG Y F,ZHOU S K,et al.Combo loss:Handling input and output imbalance in multi-organ segmentation[J]. Computerized Medical Imaging and Graphics,2019,75:24-33.

    [18] [18] LITJENS G,TOTH R,VAN DE VEN W,et al.Evaluation of prostate segmentation algorithms for MRI:The PROMISE12 challenge[J].Medical Image Analysis,2014,18(2):359-373.

    Tools

    Get Citation

    Copy Citation Text

    SANG Zijiang, SHAO Yeqin, XU Changyan. Prostate magnetic resonance image segmentation based on improved 3D UNet[J]. Journal of Optoelectronics · Laser, 2023, 34(12): 1337

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Received: Dec. 27, 2022

    Accepted: --

    Published Online: Sep. 25, 2024

    The Author Email: SHAO Yeqin (hnsyk@ntu.edu.cn)

    DOI:10.16136/j.joel.2023.12.0861

    Topics