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Inas A. Yassine
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2020 – today
- 2023
- [j5]Rasha Ramadan Z. Koko
, Inas A. Yassine
, Manal Abdel Wahed
, June K. Madete, Muhammad Ali Rushdi
:
Dynamic Construction of Outlier Detector Ensembles With Bisecting K-Means Clustering. IEEE Access 11: 24431-24447 (2023) - [c12]Peter E. Salah
, Merna Bibars
, Ayman Eldeib
, Ahmed M. Ghanem, Ahmed M. Gharib, Khaled Z. Abd-Elmoniem
, Mustafa A. Elattar
, Inas A. Yassine:
Iterative Refinement Algorithm for Liver Segmentation Ground-Truth Generation Using Fine-Tuning Weak Labels for CT and Structural MRI. MIUA 2023: 33-47 - [c11]Merna Bibars
, Peter E. Salah
, Ayman Eldeib
, Mustafa A. Elattar
, Inas A. Yassine
:
Cross-Modality Deep Transfer Learning: Application to Liver Segmentation in CT and MRI. MIUA 2023: 96-110 - 2022
- [j4]Inas A. Yassine, Ahmed M. Ghanem, Nader S. Metwalli, Ahmed H. Hamimi, Ronald Ouwerkerk, Jatin R. Matta
, Michael A. Solomon
, Jason M. Elinoff, Ahmed M. Gharib, Khaled Z. Abd-Elmoniem
:
Native-resolution myocardial principal Eulerian strain mapping using convolutional neural networks and Tagged Magnetic Resonance Imaging. Comput. Biol. Medicine 141: 105041 (2022)
2010 – 2019
- 2018
- [j3]Rami F. Algunaid, Ali H. Algumaei, Muhammad Ali Rushdi, Inas A. Yassine:
Schizophrenic patient identification using graph-theoretic features of resting-state fMRI data. Biomed. Signal Process. Control. 43: 289-299 (2018) - [c10]Ghaidaa W. Eldeeb, Nourhan Zayed, Inas A. Yassine:
Alzheimer'S Disease Classification Using Bag-Of-Words Based On Visual Pattern Of Diffusion Anisotropy For DTI Imaging. EMBC 2018: 57-60 - 2017
- [c9]Mohamed S. Elmahdy, Sara S. Abdeldayem, Inas A. Yassine:
Low quality dermal image classification using transfer learning. BHI 2017: 373-376 - 2016
- [c8]Aya F. Khalaf, Inas A. Yassine, Ahmed S. Fahmy:
Convolutional neural networks for deep feature learning in retinal vessel segmentation. ICIP 2016: 385-388 - 2015
- [j2]Aya F. Khalaf, Mohamed I. Owis, Inas A. Yassine:
A novel technique for cardiac arrhythmia classification using spectral correlation and support vector machines. Expert Syst. Appl. 42(21): 8361-8368 (2015) - [c7]Omar Emad, Inas A. Yassine, Ahmed S. Fahmy:
Automatic localization of the left ventricle in cardiac MRI images using deep learning. EMBC 2015: 683-686 - [c6]Aya F. Khalaf, Mohamed I. Owis, Inas A. Yassine:
Image features of spectral correlation function for arrhythmia classification. EMBC 2015: 5199-5202 - [c5]Aya F. Khalaf, Inas A. Yassine:
Novel features for microcalcification detection in digital mammogram images based on wavelet and statistical analysis. ICIP 2015: 1825-1829 - [c4]Aya F. Khalaf, Inas A. Yassine:
Spectral correlation analysis for microcalcification detection in digital mammogram images. ISBI 2015: 88-91 - 2014
- [c3]Aya F. Ahmed, Mohamed I. Owis, Inas A. Yassine:
Novel Bayesian classifier discriminant function optimization strategies for arrhythmia classification. BHI 2014: 693-696 - 2011
- [j1]Tim McGraw
, Takamitsu Kawai
, Inas A. Yassine
, Lierong Zhu:
Visualizing High-Order Symmetric Tensor Field Structure with Differential Operators. J. Appl. Math. 2011: 142923:1-142923:27 (2011)
2000 – 2009
- 2009
- [c2]Inas A. Yassine, Tim McGraw
:
4th Order Diffusion Tensor Interpolation with Divergence and Curl Constrained Bezier Patches. ISBI 2009: 634-637 - [c1]Tim McGraw
, Takamitsu Kawai, Inas A. Yassine, Lierong Zhu:
New Scalar Measures for Diffusion-Weighted MRI Visualization. ISVC (1) 2009: 934-943
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