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Volumn , Issue , 2017, Pages 341-344

Deep residual Hough voting for mitotic cell detection in histopathology images

Author keywords

Deep Learning; Dilated Convolution; Hough transform; Microscopy; Residual Network

Indexed keywords

CELLS; CYTOLOGY; DEEP LEARNING; HOUGH TRANSFORMS; MICROSCOPIC EXAMINATION; NETWORK ARCHITECTURE; NETWORK LAYERS;

EID: 85023195896     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2017.7950533     Document Type: Conference Paper
Times cited : (20)

References (23)
  • 1
    • 84885899176 scopus 로고    scopus 로고
    • Mitosis detection in breast cancer histology images with deep neural networks
    • Springer, 2013
    • D. C. Cireşan, A. Giusti, L. M. Gambardella, and J. Schmidhuber, "Mitosis detection in breast cancer histology images with deep neural networks, " in Proc. MICCAI 2013, pp. 411-418, Springer, 2013.
    • (2013) Proc. MICCAI , pp. 411-418
    • Cireşan, D.C.1    Giusti, A.2    Gambardella, L.M.3    Schmidhuber, J.4
  • 4
    • 84978397845 scopus 로고    scopus 로고
    • Automated mitosis detection with deep regression networks
    • IEEE, 2016
    • H. Chen, X. Wang, and P. A. Heng, "Automated mitosis detection with deep regression networks, " in Proc. IEEE ISBI 2016, pp. 1204-1207, IEEE, 2016.
    • (2016) Proc. IEEE ISBI , pp. 1204-1207
    • Chen, H.1    Wang, X.2    Heng, P.A.3
  • 5
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks, " in Proc. NIPS 2012, pp. 1097-1105, 2012.
    • (2012) Proc. NIPS 2012 , pp. 1097-1105
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 7
    • 84973879016 scopus 로고    scopus 로고
    • Learning deconvolution network for semantic segmentation
    • Dec 2015
    • H. Noh, S. Hong, and B. Han, "Learning deconvolution network for semantic segmentation, " in Proc. IEEE ICCV 2015, pp. 1520-1528, Dec 2015.
    • (2015) Proc. IEEE ICCV , pp. 1520-1528
    • Noh, H.1    Hong, S.2    Han, B.3
  • 12
    • 84055207812 scopus 로고    scopus 로고
    • Hough transform: Underestimated tool in the computer vision field
    • D. P. Nikolaev, S. M. Karpenko, I. P. Nikolaev, and P. P. Nikolayev, "Hough transform: underestimated tool in the computer vision field, " in Proc. ECMS, vol. 238, p. 246, 2008.
    • (2008) Proc. ECMS , vol.238 , pp. 246
    • Nikolaev, D.P.1    Karpenko, S.M.2    Nikolaev, I.P.3    Nikolayev, P.P.4
  • 14
    • 84968542311 scopus 로고    scopus 로고
    • Locality sensitive deep learning for detection and classification of nuclei in routine colon cancer histology images
    • K. Sirinukunwattana, S. E. A. Raza, Y.-W. Tsang, D. R. Snead, I. A. Cree, and N. M. Rajpoot, "Locality sensitive deep learning for detection and classification of nuclei in routine colon cancer histology images, " IEEE Trans. Med. Imaging., vol. 35, no. 5, pp. 1196-1206, 2016.
    • (2016) IEEE Trans. Med. Imaging , vol.35 , Issue.5 , pp. 1196-1206
    • Sirinukunwattana, K.1    Raza, S.E.A.2    Tsang, Y.-W.3    Snead, D.R.4    Cree, I.A.5    Rajpoot, N.M.6
  • 16
    • 84904163933 scopus 로고    scopus 로고
    • Dropout: A simple way to prevent neural networks from overfitting
    • N. Srivastava, G. E. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, "Dropout: A simple way to prevent neural networks from overfitting, " JMLR, vol. 15, no. 1, pp. 1929-1958, 2014.
    • (2014) JMLR , vol.15 , Issue.1 , pp. 1929-1958
    • Srivastava, N.1    Hinton, G.E.2    Krizhevsky, A.3    Sutskever, I.4    Salakhutdinov, R.5
  • 17
    • 84973911419 scopus 로고    scopus 로고
    • Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
    • K. He, X. Zhang, S. Ren, and J. Sun, "Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, " in Proc. IEEE ICCV 2015, pp. 1026-1034, 2015.
    • (2015) Proc. IEEE ICCV , pp. 1026-1034
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 18
    • 84862277874 scopus 로고    scopus 로고
    • Understanding the difficulty of training deep feedforward neural networks
    • X. Glorot and Y. Bengio, "Understanding the difficulty of training deep feedforward neural networks, " in Proc. AISTATS 2010, vol. 9, pp. 249-256, 2010.
    • (2010) Proc. AISTATS , vol.9 , pp. 249-256
    • Glorot, X.1    Bengio, Y.2
  • 19
    • 84937943470 scopus 로고    scopus 로고
    • Depth map prediction from a single image using a multi-scale deep network
    • D. Eigen, C. Puhrsch, and R. Fergus, "Depth map prediction from a single image using a multi-scale deep network, " in Proc. NIPS 2015, pp. 2366-2374, 2014.
    • (2015) Proc. NIPS , pp. 2366-2374
    • Eigen, D.1    Puhrsch, C.2    Fergus, R.3
  • 21
    • 84903773823 scopus 로고    scopus 로고
    • HEp-2 cell classification using shape index histograms with donut-shaped spatial pooling
    • A. B. L. Larsen, J. S. Vestergaard, and R. Larsen, "HEp-2 cell classification using shape index histograms with donut-shaped spatial pooling, " IEEE Trans. Med. Imaging., vol. 33, no. 7, pp. 1573-1580, 2014.
    • (2014) IEEE Trans. Med. Imaging , vol.33 , Issue.7 , pp. 1573-1580
    • Larsen, A.B.L.1    Vestergaard, J.S.2    Larsen, R.3
  • 23
    • 85023169478 scopus 로고    scopus 로고
    • Accessed: 2016-10-31
    • "TUPAC16 contest home page. " http: //tupac. Tue-image. nl/. Accessed: 2016-10-31.
    • TUPAC16 Contest Home Page


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.