DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI A Riaz, M Asad, E Alonso, G Slabaugh Journal of neuroscience methods 335, 108506, 2020 | 116 | 2020 |
Fusion of fMRI and non-imaging data for ADHD classification A Riaz, M Asad, E Alonso, G Slabaugh Computerized Medical Imaging and Graphics 65, 115-128, 2018 | 110 | 2018 |
Deep fMRI: An end-to-end deep network for classification of fMRI data A Riaz, M Asad, SMMR Al Arif, E Alonso, D Dima, P Corr, G Slabaugh 2018 ieee 15th international symposium on biomedical imaging (isbi 2018 …, 2018 | 70 | 2018 |
Monai label: A framework for ai-assisted interactive labeling of 3d medical images A Diaz-Pinto, S Alle, V Nath, Y Tang, A Ihsani, M Asad, F Pérez-García, ... Medical Image Analysis 95, 103207, 2024 | 57 | 2024 |
Fcnet: a convolutional neural network for calculating functional connectivity from functional mri A Riaz, M Asad, SMMR Al-Arif, E Alonso, D Dima, P Corr, G Slabaugh Connectomics in NeuroImaging: First International Workshop, CNI 2017, Held …, 2017 | 56 | 2017 |
KINECT DEPTH STREAM PRE-PROCESSING FOR HAND GESTURE RECOGNITION M Asad, C Abhayaratne Image Processing (ICIP), 2013 20th IEEE International Conference on, 3735-3739, 2013 | 22 | 2013 |
DeepEdit: Deep editable learning for interactive segmentation of 3D medical images A Diaz-Pinto, P Mehta, S Alle, M Asad, R Brown, V Nath, A Ihsani, ... MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, 11-21, 2022 | 18 | 2022 |
Patch-based corner detection for cervical vertebrae in X-ray images SMMR Al Arif, M Asad, M Gundry, K Knapp, G Slabaugh Signal Processing: Image Communication 59, 27-36, 2017 | 13 | 2017 |
Smartphone based guidance system for visually impaired person M Asad, W Ikram 2012 3rd International Conference on Image Processing Theory, Tools and …, 2012 | 12 | 2012 |
ECONet: Efficient convolutional online likelihood network for scribble-based interactive segmentation M Asad, L Fidon, T Vercauteren International Conference on Medical Imaging with Deep Learning, 35-47, 2022 | 10 | 2022 |
Cervical vertebral corner detection using Haar-like features and modified Hough forest SMR Al Arif, M Asad, K Knapp, M Gundry, G Slabaugh 2015 International Conference on Image Processing Theory, Tools and …, 2015 | 10 | 2015 |
Hand orientation regression using random forest for augmented reality M Asad, G Slabaugh Augmented and Virtual Reality: First International Conference, AVR 2014 …, 2014 | 10 | 2014 |
Boundary distance loss for intra-/extra-meatal segmentation of vestibular schwannoma N Wijethilake, A Kujawa, R Dorent, M Asad, A Oviedova, T Vercauteren, ... International Workshop on Machine Learning in Clinical Neuroimaging, 73-82, 2022 | 8 | 2022 |
Fastgeodis: Fast generalised geodesic distance transform M Asad, R Dorent, T Vercauteren arXiv preprint arXiv:2208.00001, 2022 | 7 | 2022 |
Learning to deblur adaptive optics retinal images A Lazareva, M Asad, G Slabaugh Image Analysis and Recognition: 14th International Conference, ICIAR 2017 …, 2017 | 7 | 2017 |
Hough forest-based corner detection for cervical spine radiographs SM Al-Arif, M Asad, K Knapp, M Gundry, GG Slabaugh | 7 | 2015 |
Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: application to surgical imaging P Li, M Asad, C Horgan, O MacCormac, J Shapey, T Vercauteren International journal of computer assisted radiology and surgery 18 (6), 981-988, 2023 | 5 | 2023 |
Learning marginalization through regression for hand orientation inference M Asad, G Slabaugh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 5 | 2016 |
Spore: Staged probabilistic regression for hand orientation inference M Asad, G Slabaugh Computer Vision and Image Understanding 161, 114-129, 2017 | 4 | 2017 |
Pairwise mixture model for unmixing partial volume effect in multi-voxel MR spectroscopy of brain tumour patients N Olliverre, M Asad, G Yang, F Howe, G Slabaugh Medical Imaging 2017: Computer-Aided Diagnosis 10134, 449-461, 2017 | 4 | 2017 |