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ORCIDShahab Aslani
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2020 – today
- 2024
[j4]Shahab Aslani, Pavan Alluri, Eyjolfur Gudmundsson, Edward Chandy, John McCabe, Anand Devaraj, Carolyn Horst, Sam M. Janes, Rahul Chakkara, Daniel C. Alexander
, Arjun Nair, Joseph Jacob:
Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning. Comput. Medical Imaging Graph. 116: 102399 (2024)- 2023
- [i6]Yaozhi Lu, Shahab Aslani, An Zhao, Ahmed H. Shahin, David Barber, Mark Emberton, Daniel C. Alexander, Joseph Jacob:
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study. CoRR abs/2303.10789 (2023) - [i5]Ekin Yagis, Shahab Aslani, Yashvardhan Jain, Yang Zhou, Shahrokh Rahmani, Joseph Brunet, Alexandre Bellier, Christopher Werlein, Maximilian Ackermann, Danny Jonigk, Paul Tafforeau, Peter D. Lee, Claire L. Walsh:
Deep Learning for Vascular Segmentation and Applications in Phase Contrast Tomography Imaging. CoRR abs/2311.13319 (2023) - 2022
- [j3]Yaozhi Lu, Shahab Aslani, Mark Emberton, Daniel C. Alexander, Joseph Jacob:
Deep Learning-Based Long Term Mortality Prediction in the National Lung Screening Trial. IEEE Access 10: 34369-34378 (2022) - [c4]Shahab Aslani, Watjana Lilaonitkul, Vaishnavi Gnanananthan, Divya Raj, Bojidar Rangelov, Alexandra L. Young, Yipeng Hu, Paul Taylor, Daniel C. Alexander, Joseph Jacob:
Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors. MICAD 2022: 245-254 - [i4]Shahab Aslani, Pavan Alluri, Eyjolfur Gudmundsson, Edward Chandy, John McCabe, Anand Devaraj, Carolyn Horst, Sam M. Janes, Rahul Chakkara, Arjun Nair, Daniel C. Alexander, SUMMIT consortium, Joseph Jacob:
Enhancing Cancer Prediction in Challenging Screen-Detected Incident Lung Nodules Using Time-Series Deep Learning. CoRR abs/2203.16606 (2022) - [i3]Shahab Aslani, Watjana Lilaonitkul, Vaishnavi Gnanananthan, Divya Raj, Bojidar Rangelov, Alexandra L. Young, Yipeng Hu, Paul Taylor, Daniel C. Alexander, Joseph Jacob:
Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors. CoRR abs/2208.10320 (2022) - 2020
- [b1]Shahab Aslani:
Deep learning approaches for segmentation of multiple sclerosis lesions on brain MRI. University of Genoa, Italy, 2020 - [c3]Shahab Aslani, Vittorio Murino, Michael Dayan, Roger C. Tam, Diego Sona, Ghassan Hamarneh:
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI. ISBI 2020: 781-785
2010 – 2019
- 2019
- [j2]Shahab Aslani, Michael Dayan, Loredana Storelli, Massimo Filippi, Vittorio Murino, Maria Assunta Rocca, Diego Sona:
Multi-branch convolutional neural network for multiple sclerosis lesion segmentation. NeuroImage 196: 1-15 (2019) - [c2]Muhammad Usman Akbar, Shahab Aslani, Vittorio Murino, Diego Sona:
Multiple Organs Segmentation in Abdomen CT Scans Using a Cascade of CNNs. ICIAP (1) 2019: 509-516 - [i2]Shahab Aslani, Vittorio Murino, Michael Dayan, Roger C. Tam, Diego Sona, Ghassan Hamarneh:
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI. CoRR abs/1910.10035 (2019) - 2018
- [c1]Shahab Aslani, Michael Dayan, Vittorio Murino, Diego Sona:
Deep 2D Encoder-Decoder Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation in Brain MRI. BrainLes@MICCAI (1) 2018: 132-141 - [i1]Shahab Aslani, Michael Dayan, Loredana Storelli, Massimo Filippi, Vittorio Murino, Maria Assunta Rocca, Diego Sona:
Multi-branch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation. CoRR abs/1811.02942 (2018) - 2016
- [j1]Shahab Aslani, Haldun Sarnel:
A new supervised retinal vessel segmentation method based on robust hybrid features. Biomed. Signal Process. Control. 30: 1-12 (2016)
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