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Journal Articles
- 2019
[j2]Fatemeh Taheri Dezaki
, Zhibin Liao, Christina Luong, Hany Girgis, Neeraj Dhungel, Amir H. Abdi, Delaram Behnami, Ken Gin, Robert Rohling, Purang Abolmaesumi, Teresa Tsang:
Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss. IEEE Trans. Medical Imaging 38(8): 1821-1832 (2019)- 2017
- [j1]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
A deep learning approach for the analysis of masses in mammograms with minimal user intervention. Medical Image Anal. 37: 114-128 (2017)
Conference and Workshop Papers
- 2019
- [c10]Hooman Vaseli, Zhibin Liao, Amir H. Abdi, Hany Girgis, Delaram Behnami, Christina Luong, Fatemeh Taheri Dezaki, Neeraj Dhungel, Robert Rohling, Ken Gin, Purang Abolmaesumi, Teresa Tsang:
Designing lightweight deep learning models for echocardiography view classification. Medical Imaging: Image-Guided Procedures 2019: 109510F - 2017
- [c9]Jaime S. Cardoso, Nuno Marques, Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features. ICIP 2017: 1737-1741 - [c8]Hang Min, Shekhar S. Chandra, Neeraj Dhungel, Stuart Crozier, Andrew P. Bradley:
Multi-scale mass segmentation for mammograms via cascaded random forests. ISBI 2017: 113-117 - [c7]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Fully automated classification of mammograms using deep residual neural networks. ISBI 2017: 310-314 - [c6]Fatemeh Taheri Dezaki, Neeraj Dhungel, Amir H. Abdi, Christina Luong, Teresa Tsang, John Jue, Ken Gin, Dale Hawley, Robert Rohling, Purang Abolmaesumi:
Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms. DLMIA/ML-CDS@MICCAI 2017: 100-108 - 2016
- [c5]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
The Automated Learning of Deep Features for Breast Mass Classification from Mammograms. MICCAI (2) 2016: 106-114 - 2015
- [c4]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests. DICTA 2015: 1-8 - [c3]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Deep structured learning for mass segmentation from mammograms. ICIP 2015: 2950-2954 - [c2]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms. ISBI 2015: 760-763 - [c1]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms. MICCAI (1) 2015: 605-612
Parts in Books or Collections
- 2017
- [p1]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms. Deep Learning and Convolutional Neural Networks for Medical Image Computing 2017: 225-240
Informal and Other Publications
- 2016
- [i2]Zhi Lu, Gustavo Carneiro, Neeraj Dhungel, Andrew P. Bradley:
Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach. CoRR abs/1610.02251 (2016) - 2014
- [i1]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Deep Structured learning for mass segmentation from Mammograms. CoRR abs/1410.7454 (2014)
Coauthor Index
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