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Neeraj Dhungel
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A deep learning approach for the analysis of masses in mammograms with minimal user intervention
N Dhungel, G Carneiro, AP Bradley
Medical image analysis 37, 114-128, 2017
3532017
Automated Mass Detection in Mammograms using Cascaded Deep Learning and Random Forests
N Dhungel, G Carneiro, AP Bradley
2015 International Conference on Digital Image Computing: Techniques and …, 2015
2832015
Deep learning and structured prediction for the segmentation of mass in mammograms
N Dhungel, G Carneiro, AP Bradley
International Conference on Medical image computing and computer-assisted …, 2015
1962015
The automated learning of deep features for breast mass classification from mammograms
N Dhungel, G Carneiro, AP Bradley
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016
1672016
FULLY AUTOMATED CLASSIFICATION OF MAMMOGRAMS USING DEEP RESIDUAL NEURAL NETWORKS
N Dhungel, G Carneiro, AP Bradley
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017
1082017
Deep Structured learning for mass segmentation from Mammograms
N Dhungel, G Carneiro, AP Bradley
12th IEEE International Conference on Image Processing, ICIP, 2950--2954, 2015
852015
Cardiac phase detection in echocardiograms with densely gated recurrent neural networks and global extrema loss
FT Dezaki, Z Liao, C Luong, H Girgis, N Dhungel, AH Abdi, D Behnami, ...
IEEE transactions on medical imaging 38 (8), 1821-1832, 2018
802018
TREE RE-WEIGHTED BELIEF PROPAGATION USING DEEP LEARNING POTENTIALS FOR MASS SEGMENTATION FROM MAMMOGRAMS
N Dhungel, G Carneiro, AP Bradley
12th IEEE International Symposium on Biomedical Imaging, ISBI, 760-763, 2015
372015
Designing lightweight deep learning models for echocardiography view classification
H Vaseli, Z Liao, AH Abdi, H Girgis, D Behnami, C Luong, FT Dezaki, ...
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and …, 2019
332019
Deep residual recurrent neural networks for characterisation of cardiac cycle phase from echocardiograms
FT Dezaki, N Dhungel, AH Abdi, C Luong, T Tsang, J Jue, K Gin, ...
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
322017
Multi-scale mass segmentation for mammograms via cascaded random forests
H Min, SS Chandra, N Dhungel, S Crozier, AP Bradley
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017
172017
Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features
JS Cardoso, N Marques, N Dhungel, G Carneiro, AP Bradley
2017 IEEE International Conference on Image Processing (ICIP), 1737-1741, 2017
152017
Automated detection of individual micro-calcifications from mammograms using a multi-stage cascade approach
Z Lu, G Carneiro, N Dhungel, AP Bradley
arXiv preprint arXiv:1610.02251, 2016
132016
Agreement of anthropometric and body composition measures predicted from 2D smartphone images and body impedance scales with criterion methods
A Nana, JMD Staynor, S Arlai, A El-Sallam, N Dhungel, MK Smith
Obesity Research & Clinical Practice 16 (1), 37-43, 2022
122022
Combining deep learning and structured prediction for segmenting masses in mammograms
N Dhungel, G Carneiro, AP Bradley
Deep Learning and Convolutional Neural Networks for Medical Image Computing …, 2017
82017
Automated detection, segmentation and classification of masses from mammograms using deep learning
N Dhungel
12016
A Deep Learning approach to fully automated analysis of Masses in Mammograms
N Dhungel, G Carneiro, AP Bradley
Automated Detection, Segmentation and Classification of Masses from …, 2016
2016
A New QRS Detection Algorithm Based on Combined Fuzzy Logic and Wavelet Technique
E Timoshenko, N Dhungel
5th European Conference of the International Federation for Medical and …, 2012
2012
Three-dimensional localization of brain bioelectric activity in gambling addiction and epilepsy
N Dhungel, E Timoshenko
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