Deep learning for image-based cancer detection and diagnosis - A survey

被引:302
作者
Hu, Zilong [1 ]
Tang, Jinshan [1 ,2 ,3 ]
Wang, Ziming [2 ]
Zhang, Kai [1 ,3 ]
Zhang, Ling [1 ]
Sun, Qingling [4 ]
机构
[1] Michigan Technol Univ, Sch Technol, Houghton, MI 49931 USA
[2] Michigan Technol Univ, Dept Elect & Comp Engn, Houghton, MI 49931 USA
[3] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430065, Hubei, Peoples R China
[4] Sun Technol & Serv LLC, Clinton, MS 39056 USA
基金
美国国家卫生研究院;
关键词
BRAIN-TUMOR SEGMENTATION; CONVOLUTIONAL NEURAL-NETWORK; COMPUTER-AIDED DIAGNOSIS; FALSE-POSITIVE REDUCTION; LUNG NODULE; MITOSIS DETECTION; CLASSIFICATION; ALGORITHMS; DATABASE; MASSES;
D O I
10.1016/j.patcog.2018.05.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we aim to provide a survey on the applications of deep learning for cancer detection and diagnosis and hope to provide an overview of the progress in this field. In the survey, we firstly provide an overview on deep learning and the popular architectures used for cancer detection and diagnosis. Especially we present four popular deep learning architectures, including convolutional neural networks, fully convolutional networks, auto-encoders, and deep belief networks in the survey. Secondly, we provide a survey on the studies exploiting deep learning for cancer detection and diagnosis. The surveys in this part are organized based on the types of cancers. Thirdly, we provide a summary and comments on the recent work on the applications of deep learning to cancer detection and diagnosis and propose some future research directions. (C) 2018 Published by Elsevier Ltd.
引用
收藏
页码:134 / 149
页数:16
相关论文
共 143 条
  • [121] Tao Xu, 2016, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016. 19th International Conference. Proceedings: LNCS 9901, P115, DOI 10.1007/978-3-319-46723-8_14
  • [122] An automatic method to discriminate malignant masses from normal tissue in digital mammograms
    te Brake, GM
    Karssemeijer, N
    Hendriks, JHCL
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2000, 45 (10) : 2843 - 2857
  • [123] Global Cancer Statistics, 2012
    Torre, Lindsey A.
    Bray, Freddie
    Siegel, Rebecca L.
    Ferlay, Jacques
    Lortet-Tieulent, Joannie
    Jemal, Ahmedin
    [J]. CA-A CANCER JOURNAL FOR CLINICIANS, 2015, 65 (02) : 87 - 108
  • [124] Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR
    Tustison, Nicholas J.
    Shrinidhi, K. L.
    Wintermark, Max
    Durst, Christopher R.
    Kandel, Benjamin M.
    Gee, James C.
    Grossman, Murray C.
    Avants, Brian B.
    [J]. NEUROINFORMATICS, 2015, 13 (02) : 209 - 225
  • [125] Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study
    van Ginneken, Bram
    Armato, Samuel G., III
    de Hoop, Bartjan
    van Amelsvoort-van de Vorst, Saskia
    Duindam, Thomas
    Niemeijer, Meindert
    Murphy, Keelin
    Schilham, Arnold
    Retico, Alessandra
    Fantacci, Maria Evelina
    Camarlinghi, Niccolo
    Bagagli, Francesco
    Gori, Ilaria
    Hara, Takeshi
    Fujita, Hiroshi
    Gargano, Gianfranco
    Bellotti, Roberto
    Tangaro, Sabina
    Bolanos, Lourdes
    De Carlo, Francesco
    Cerello, Piergiorgio
    Cheran, Sorin Cristian
    Lopez Torres, Ernesto
    Prokop, Mathias
    [J]. MEDICAL IMAGE ANALYSIS, 2010, 14 (06) : 707 - 722
  • [126] Assessment of algorithms for mitosis detection in breast cancer histopathology images
    Veta, Mitko
    van Diest, Paul J.
    Willems, Stefan M.
    Wang, Haibo
    Madabhushi, Anant
    Cruz-Roa, Angel
    Gonzalez, Fabio
    Larsen, Anders B. L.
    Vestergaard, Jacob S.
    Dahl, Anders B.
    Ciresan, Dan C.
    Schmidhuber, Juergen
    Giusti, Alessandro
    Gambardella, Luca M.
    Tek, F. Boray
    Walter, Thomas
    Wang, Ching-Wei
    Kondo, Satoshi
    Matuszewski, Bogdan J.
    Precioso, Frederic
    Snell, Violet
    Kittler, Josef
    de Campos, Teofilo E.
    Khan, Adnan M.
    Rajpoot, Nasir M.
    Arkoumani, Evdokia
    Lacle, Miangela M.
    Viergever, Max A.
    Pluim, Josien P. W.
    [J]. MEDICAL IMAGE ANALYSIS, 2015, 20 (01) : 237 - 248
  • [127] Lung nodule classification using deep feature fusion in chest radiography
    Wang, Changmiao
    Elazab, Ahmed
    Wu, Jianhuang
    Hu, Qingmao
    [J]. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2017, 57 : 10 - 18
  • [128] Computer-aided detection of breast masses on full field digital mammogranris
    Wei, J
    Sahiner, B
    Hadjiiski, LM
    Chan, HP
    Petrick, N
    Helvie, MA
    Roubidoux, MA
    Ge, J
    Zhou, C
    [J]. MEDICAL PHYSICS, 2005, 32 (09) : 2827 - 2838
  • [129] Wichakam I, 2016, INT CONF KNOWL SMART, P239, DOI 10.1109/KST.2016.7440527
  • [130] An Automatic Learning-Based Framework for Robust Nucleus Segmentation
    Xing, Fuyong
    Xie, Yuanpu
    Yang, Lin
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2016, 35 (02) : 550 - 566