Taimur Hassan
Taimur Hassan
Khalifa University (KU), National University of Sciences and Technology (NUST)
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Structure tensor based automated detection of macular edema and central serous retinopathy using optical coherence tomography images
B Hassan, G Raja, T Hassan, MU Akram
JOSA A 33 (4), 455-463, 2016
Review of OCT and fundus images for detection of Macular Edema
T Hassan, MU Akram, B Hassan, A Nasim, SA Bazaz
2015 IEEE International Conference on Imaging Systems and Techniques (IST), 1-4, 2015
Automated diagnosis of macular edema and central serous retinopathy through robust reconstruction of 3D retinal surfaces
AM Syed, T Hassan, MU Akram, S Naz, S Khalid
Computer methods and programs in biomedicine 137, 1-10, 2016
Automated segmentation of subretinal layers for the detection of macular edema
T Hassan, MU Akram, B Hassan, AM Syed, SA Bazaz
Applied optics 55 (3), 454-461, 2016
Fully automated robust system to detect retinal edema, central serous chorioretinopathy, and age related macular degeneration from optical coherence tomography images
S Khalid, MU Akram, T Hassan, A Nasim, A Jameel
BioMed research international 2017, 2017
Data on fundus images for vessels segmentation, detection of hypertensive retinopathy, diabetic retinopathy and papilledema
MU Akram, S Akbar, T Hassan, SG Khawaja, U Yasin, I Basit
Data in brief 29, 105282, 2020
Deep ensemble learning based objective grading of macular edema by extracting clinically significant findings from fused retinal imaging modalities
B Hassan, T Hassan, B Li, R Ahmed, O Hassan
Sensors 19 (13), 2970, 2019
Automated segmentation and quantification of drusen in fundus and optical coherence tomography images for detection of ARMD
S Khalid, MU Akram, T Hassan, A Jameel, T Khalil
Journal of digital imaging 31 (4), 464-476, 2018
Deep structure tensor graph search framework for automated extraction and characterization of retinal layers and fluid pathology in retinal SD-OCT scans
T Hassan, MU Akram, MF Masood, U Yasin
Computers in biology and medicine 105, 112-124, 2019
Fully convolutional neural network for lungs segmentation from chest X-rays
R Rashid, MU Akram, T Hassan
International Conference Image Analysis and Recognition, 71-80, 2018
Detecting prohibited items in X-ray images: a contour proposal learning approach
T Hassan, M Bettayeb, S Akçay, S Khan, M Bennamoun, N Werghi
2020 IEEE International Conference on Image Processing (ICIP), 2016-2020, 2020
Fully automated multi-resolution channels and multithreaded spectrum allocation protocol for IoT based sensor nets
T Hassan, S Aslam, JW Jang
IEEE Access 6, 22545-22556, 2018
Clinically verified hybrid deep learning system for retinal ganglion cells aware grading of glaucomatous progression
H Raja, T Hassan, MU Akram, N Werghi
IEEE Transactions on Biomedical Engineering 68 (7), 2140-2151, 2020
Fully automated diagnosis of papilledema through robust extraction of vascular patterns and ocular pathology from fundus photographs
KN Fatima, T Hassan, MU Akram, M Akhtar, WH Butt
Biomedical optics express 8 (2), 1005-1024, 2017
HDAT: web-based high-throughput screening data analysis tools
R Liu, T Hassan, R Rallo, Y Cohen
Computational Science & Discovery 6 (1), 014006, 2013
Fully automated detection, grading and 3D modeling of maculopathy from OCT volumes
B Hassan, T Hassan
2019 2nd International Conference on Communication, Computing and Digital …, 2019
Multilayered deep structure tensor delaunay triangulation and morphing based automated diagnosis and 3D presentation of human macula
T Hassan, MU Akram, M Akhtar, SA Khan, U Yasin
Journal of medical systems 42 (11), 1-17, 2018
BIOMISA retinal image database for macular and ocular syndromes
T Hassan, MU Akram, MF Masood, U Yasin
International Conference Image Analysis and Recognition, 695-705, 2018
AVRDB: annotated dataset for vessel segmentation and calculation of arteriovenous ratio
S Akbar, T Hassan, MU Akram, UU Yasin, I Basit
Proceedings of the 21th Int’l Conf on Image Processing, Computer Vision …, 2017
Joint segmentation and quantification of chorioretinal biomarkers in optical coherence tomography scans: A deep learning approach
B Hassan, S Qin, T Hassan, R Ahmed, N Werghi
IEEE Transactions on Instrumentation and Measurement 70, 1-17, 2021
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