Enhanced Rotated Mask R-CNN for Chromosome Segmentation

被引:6
|
作者
Wang, Penglei [1 ]
Hu, Wenjing [2 ]
Zhang, Jiping [1 ]
Wen, Yaofeng [3 ]
Xu, Chenming [2 ]
Qian, Dahong [3 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Biomed Engn, Shanghai, Peoples R China
[2] Int Peace Matern & Child Hlth Hosp China, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, Inst Med Robot, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1109/EMBC46164.2021.9630695
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Karyotyping is an important process for finding chromosome abnormalities that could cause genetic disorders. This process first requires cytogeneticists to arrange each chromosome from the metaphase image to generate the karyogram. In this process, chromosome segmentation plays an important role and it is directly related to whether the karyotyping can be achieved. The key to achieving accurate chromosome segmentation is to effectively segment the multiple touching and overlapping chromosomes at the same time identify the isolated chromosomes. This paper proposes a method named Enhanced Rotated Mask R-CNN for automatic chromosome segmentation and classification. The Enhanced Rotated Mask R-CNN method can not only accurately segment and classify the isolated chromosomes in metaphase images but also effectively alleviate the problem of inaccurate segmentation for touching and overlapping chromosomes. Experiments show that the proposed approach achieves competitive performances with 49.52 AP on multi-class evaluation and 69.96 AP on binary-class evaluation for chromosome segmentation.
引用
收藏
页码:2769 / 2772
页数:4
相关论文
共 50 条
  • [1] Enhanced Mask R-CNN for herd segmentation
    Bello, Rotimi-Williams
    Mohamed, Ahmad Sufril Azlan
    Talib, Abdullah Zawawi
    [J]. INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, 2021, 14 (04) : 238 - 244
  • [2] Nuclei R-CNN: Improve Mask R-CNN for Nuclei Segmentation
    Lv, Guofeng
    Wen, Ke
    Wu, Zheng
    Jin, Xu
    An, Hong
    He, Jie
    [J]. 2019 2ND IEEE INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SIGNAL PROCESSING (ICICSP), 2019, : 357 - 362
  • [3] SE-Mask R-CNN: An improved Mask R-CNN for apple detection and segmentation
    Liu, Yikun
    Yang, Gongping
    Huang, Yuwen
    Yin, Yilong
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 41 (06) : 6715 - 6725
  • [4] IEMask R-CNN: Information-Enhanced Mask R-CNN
    Bi, Xiuli
    Hu, Jinwu
    Xiao, Bin
    Li, Weisheng
    Gao, Xinbo
    [J]. IEEE TRANSACTIONS ON BIG DATA, 2023, 9 (02) : 688 - 700
  • [5] An Enhanced Mask R-CNN Approach for Pulmonary Embolism Detection and Segmentation
    Dogan, Kamil
    Selcuk, Turab
    Alkan, Ahmet
    [J]. DIAGNOSTICS, 2024, 14 (11)
  • [6] An Improved Mask R-CNN Model for Multiorgan Segmentation
    Shu, Jian-Hua
    Nian, Fu-Dong
    Yu, Ming-Hui
    Li, Xu
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020
  • [7] Potato Detection and Segmentation Based on Mask R-CNN
    Lee H.-S.
    Shin B.-S.
    [J]. Journal of Biosystems Engineering, 2020, 45 (4) : 233 - 238
  • [8] PULMOSEGNET: CT NODULE SEGMENTATION WITH MASK R-CNN
    Thirupathi, P.
    Ram, Nambi U.
    Kumar, Karthick, V
    Malathi, M.
    [J]. 2024 5TH INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN INFORMATION TECHNOLOGY, ICITIIT 2024, 2024,
  • [9] An Improved Mask R-CNN Method for Weed Segmentation
    Jin, Shangzhu
    Dai, Haojun
    Peng, Jun
    He, Yuanmin
    Zhu, Min
    Yu, Wencheng
    Li, Qingxia
    [J]. 2022 IEEE 17TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2022, : 1430 - 1435
  • [10] Mask R-CNN
    He, Kaiming
    Gkioxari, Georgia
    Dollar, Piotr
    Girshick, Ross
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 42 (02) : 386 - 397