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Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique
Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique
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Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique

Greenspan, Hayit ; van Ginneken, Bram ; Summers, Ronald M.

IEEE transactions on medical imaging, 2016-05, Vol.35 (5), p.1153-1159

IEEE

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Multiple instance learning for histopathological breast cancer image classification
Multiple instance learning for histopathological breast cancer image classification
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Multiple instance learning for histopathological breast cancer image classification

Sudharshan, P.J. ; Petitjean, Caroline ; Spanhol, Fabio ; Oliveira, Luiz Eduardo ; Heutte, Laurent ; Honeine, Paul

Expert systems with applications, 2019-03, Vol.117, p.103-111 [Periódico revisado por pares]

New York: Elsevier Ltd

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3
Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data
Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data
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Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data

Hoo-Chang Shin ; Orton, M. R. ; Collins, D. J. ; Doran, S. J. ; Leach, M. O.

IEEE transactions on pattern analysis and machine intelligence, 2013-08, Vol.35 (8), p.1930-1943 [Periódico revisado por pares]

United States: IEEE

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4
Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review-Current Status and Future Potential
Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review-Current Status and Future Potential
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Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review-Current Status and Future Potential

Irshad, Humayun ; Veillard, Antoine ; Roux, Ludovic ; Racoceanu, Daniel

IEEE reviews in biomedical engineering, 2014, Vol.7, p.97-114 [Periódico revisado por pares]

United States: IEEE

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5
A method for normalizing histology slides for quantitative analysis
A method for normalizing histology slides for quantitative analysis
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A method for normalizing histology slides for quantitative analysis

Macenko, M. ; Niethammer, M. ; Marron, J.S. ; Borland, D. ; Woosley, J.T. ; Xiaojun Guan ; Schmitt, C. ; Thomas, N.E.

2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009, p.1107-1110

IEEE

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6
Mutual-information-based registration of medical images: a survey
Mutual-information-based registration of medical images: a survey
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Mutual-information-based registration of medical images: a survey

Pluim, J.P.W. ; Maintz, J.B.A. ; Viergever, M.A.

IEEE transactions on medical imaging, 2003-08, Vol.22 (8), p.986-1004

New York, NY: IEEE

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7
Automatic Cell Detection in Bright-Field Microscope Images Using SIFT, Random Forests, and Hierarchical Clustering
Automatic Cell Detection in Bright-Field Microscope Images Using SIFT, Random Forests, and Hierarchical Clustering
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Automatic Cell Detection in Bright-Field Microscope Images Using SIFT, Random Forests, and Hierarchical Clustering

Mualla, Firas ; Scholl, Simon ; Sommerfeldt, Bjorn ; Maier, Andreas ; Hornegger, Joachim

IEEE transactions on medical imaging, 2013-12, Vol.32 (12), p.2274-2286

United States: IEEE

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8
Untangling cell tracks: Quantifying cell migration by time lapse image data analysis
Untangling cell tracks: Quantifying cell migration by time lapse image data analysis
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Untangling cell tracks: Quantifying cell migration by time lapse image data analysis

Svensson, Carl‐Magnus ; Medyukhina, Anna ; Belyaev, Ivan ; Al‐Zaben, Naim ; Figge, Marc Thilo

Cytometry. Part A, 2018-03, Vol.93 (3), p.357-370 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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9
Minimum mean brightness error bi-histogram equalization in contrast enhancement
Minimum mean brightness error bi-histogram equalization in contrast enhancement
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Minimum mean brightness error bi-histogram equalization in contrast enhancement

Soong-Der Chen ; Ramli, A.R.

IEEE transactions on consumer electronics, 2003-11, Vol.49 (4), p.1310-1319 [Periódico revisado por pares]

New York: IEEE

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10
Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features
Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features
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Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features

Hawkins, Samuel H. ; Korecki, John N. ; Balagurunathan, Yoganand ; Yuhua Gu ; Kumar, Virendra ; Basu, Satrajit ; Hall, Lawrence O. ; Goldgof, Dmitry B. ; Gatenby, Robert A. ; Gillies, Robert J.

IEEE access, 2014, Vol.2, p.1418-1426 [Periódico revisado por pares]

Piscataway: IEEE

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