-
1
-
-
84896123432
-
Weakly supervised histopathology cancer image segmentation and classification
-
Y. Xu, J. Zhu, E. I. Chang, M. Lai, and Z. Tu, "Weakly supervised histopathology cancer image segmentation and classification, " Med. Image Anal., vol. 18, no. 3, pp. 591-604, 2014.
-
(2014)
Med. Image Anal
, vol.18
, Issue.3
, pp. 591-604
-
-
Xu, Y.1
Zhu, J.2
Chang, E.I.3
Lai, M.4
Tu, Z.5
-
2
-
-
84922337078
-
Empowering multiple instance histopathology cancer diagnosis by cell graphs
-
M. Kandemir, C. Zhang, and F. A. Hamprecht, "Empowering multiple instance histopathology cancer diagnosis by cell graphs, " MICCAI, pp. 228-235, 2014.
-
(2014)
MICCAI
, pp. 228-235
-
-
Kandemir, M.1
Zhang, C.2
Hamprecht, F.A.3
-
3
-
-
84911451297
-
Classification of histology sections via multispectral convolutional sparse coding
-
Y. Zhou, H. Chang, K. Barner, P. Spellman, and B. Parvin, "Classification of histology sections via multispectral convolutional sparse coding, " CVPR, pp. 3081-3088, 2014.
-
(2014)
CVPR
, pp. 3081-3088
-
-
Zhou, Y.1
Chang, H.2
Barner, K.3
Spellman, P.4
Parvin, B.5
-
4
-
-
84947607834
-
Automatic diagnosis of ovarian carcinomas via sparse multiresolution tissue representation
-
A. BenTaieb, H. Li-Chang, D. Huntsman, and G. Hamarneh, "Automatic diagnosis of ovarian carcinomas via sparse multiresolution tissue representation, " MICCAI, pp. 629-636, 2015.
-
(2015)
MICCAI
, pp. 629-636
-
-
BenTaieb, A.1
Li-Chang, H.2
Huntsman, D.3
Hamarneh, G.4
-
5
-
-
84989954169
-
Histopathology image categorization with discriminative dimension reduction of fisher vectors
-
Y. Song, Q. Li, H. Huang, D. Feng, M. Chen, and W. Cai, "Histopathology image categorization with discriminative dimension reduction of fisher vectors, " ECCV Workshops, pp. 306-317, 2016.
-
(2016)
ECCV Workshops
, pp. 306-317
-
-
Song, Y.1
Li, Q.2
Huang, H.3
Feng, D.4
Chen, M.5
Cai, W.6
-
6
-
-
85007257318
-
Breast cancer histopathological image classification using convolutional neural networks
-
F. Spanhol, L. S. Oliveira, C. Petitjean, and L. Heutte, "Breast cancer histopathological image classification using convolutional neural networks, " IJCNN, pp. 1-8, 2016.
-
(2016)
IJCNN
, pp. 1-8
-
-
Spanhol, F.1
Oliveira, L.S.2
Petitjean, C.3
Heutte, L.4
-
7
-
-
84951788063
-
Neutrophils identification by deep learning and voronoi diagram of clusters
-
J. Wang, J. D. MacKenzie, R. Ramachandran, and D. Z. Chen, "Neutrophils identification by deep learning and voronoi diagram of clusters, " MICCAI, pp. 226-233, 2015.
-
(2015)
MICCAI
, pp. 226-233
-
-
Wang, J.1
MacKenzie, J.D.2
Ramachandran, R.3
Chen, D.Z.4
-
8
-
-
84959431409
-
An automatic learning-based framework for robust nucleus segmentation
-
F. Xing, Y. Xie, and L. Yang, "An automatic learning-based framework for robust nucleus segmentation, " IEEE Trans. Med. Imag., vol. 35, no. 2, pp. 550-566, 2016.
-
(2016)
IEEE Trans. Med. Imag
, vol.35
, Issue.2
, pp. 550-566
-
-
Xing, F.1
Xie, Y.2
Yang, L.3
-
9
-
-
84878919540
-
Imagenet classification with deep convolutional neural networks
-
A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks, " NIPS, pp. 1-9, 2012.
-
(2012)
NIPS
, pp. 1-9
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
10
-
-
84951761386
-
Unregistered multiview mammogram analysis with pre-trained deep learning models
-
G. Carneiro, J. Nascimento, and A. P. Bradley, "Unregistered multiview mammogram analysis with pre-trained deep learning models, " MICCAI, pp. 652-660, 2015.
-
(2015)
MICCAI
, pp. 652-660
-
-
Carneiro, G.1
Nascimento, J.2
Bradley, A.P.3
-
11
-
-
84969962996
-
Deep convolutional neural networks for computer-aided detection: CNN architecture, dataset characteristics and transfer learning
-
H. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, and R. M. Summers, "Deep convolutional neural networks for computer-aided detection: CNN architecture, dataset characteristics and transfer learning, " IEEE Trans. Med. Imag., vol. 35, no. 5, pp. 1285-1298, 2016.
-
(2016)
IEEE Trans. Med. Imag
, vol.35
, Issue.5
, pp. 1285-1298
-
-
Shin, H.1
Roth, H.R.2
Gao, M.3
Lu, L.4
Xu, Z.5
Nogues, I.6
Yao, J.7
Mollura, D.8
Summers, R.M.9
-
12
-
-
78149348137
-
Improving the fisher kernel for large-scale image classification
-
F. Perronnin, J. Sanchez, and T. Mensink, "Improving the fisher kernel for large-scale image classification, " ECCV, pp. 143-156, 2010.
-
(2010)
ECCV
, pp. 143-156
-
-
Perronnin, F.1
Sanchez, J.2
Mensink, T.3
-
13
-
-
84978091692
-
A dataset for breast cancer histopathological image classification
-
F. Spanhol, L. S. Oliveira, C. Petitjean, and L. Heutte, "A dataset for breast cancer histopathological image classification, " IEEE Trans. Biomed. Eng, vol. 63, no. 7, pp. 1455-1462, 2016.
-
(2016)
IEEE Trans. Biomed. Eng
, vol.63
, Issue.7
, pp. 1455-1462
-
-
Spanhol, F.1
Oliveira, L.S.2
Petitjean, C.3
Heutte, L.4
-
14
-
-
84950120533
-
Deep filter banks for texture recognition and segmentation
-
M. Cimpoi, S. Maji, and A. Vedaldi, "Deep filter banks for texture recognition and segmentation, " CVPR, pp. 3828-3836, 2015.
-
(2015)
CVPR
, pp. 3828-3836
-
-
Cimpoi, M.1
Maji, S.2
Vedaldi, A.3
-
15
-
-
85083953063
-
Very deep convolutional networks for large-scale image recognition
-
arXiv: 1409. 1556
-
K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition, " ICLR, arXiv: 1409. 1556, 2015.
-
(2015)
ICLR
-
-
Simonyan, K.1
Zisserman, A.2
-
16
-
-
84986277601
-
Visualizing and understanding deep texture representations
-
T. Lin and S. Maji, "Visualizing and understanding deep texture representations, " CVPR, pp. 2791-2799, 2016.
-
(2016)
CVPR
, pp. 2791-2799
-
-
Lin, T.1
Maji, S.2
|