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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
2762017
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
2342015
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
1602015
The automated learning of deep features for breast mass classification from mammograms
N Dhungel, G Carneiro, AP Bradley
International Conference on Medical Image Computing and Computer-Assisted …, 2016
1362016
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
862017
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
662015
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
512018
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
292015
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
232019
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
222017
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
152017
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
132017
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
102016
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
62017
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
32022
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 …, 2011
2011
Three-dimensional localization of brain bioelectric activity in gambling addiction and epilepsy
N Dhungel, E Timoshenko
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