189 citations · 196 across the 7 of their papers we have counts for
8 papers
Association of Progressive PPFE and Mortality in Lung Cancer Screening Cohorts
Shahab Aslani, Mehran Azimbagirad, Daryl Cheng +16
Background: Pleuroparenchymal fibroelastosis (PPFE) is an upper lobe predominant fibrotic lung abnormality associated with increased mortality in established interstitial lung dise…
A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs
Niccolò McConnell, Pardeep Vasudev, Daisuke Yamada +13
Low-dose computed tomography (LDCT) imaging employed in lung cancer screening (LCS) programs is increasing in uptake worldwide. LCS programs herald a generational opportunity to si…
Deep Learning for Vascular Segmentation and Applications in Phase Contrast Tomography Imaging
Ekin Yagis, Shahab Aslani, Yashvardhan Jain +10
Automated blood vessel segmentation is vital for biomedical imaging, as vessel changes indicate many pathologies. Still, precise segmentation is difficult due to the complexity of…
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study
Yaozhi Lu, Shahab Aslani, An Zhao +5
In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respirat…
Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors
Shahab Aslani, Watjana Lilaonitkul, Vaishnavi Gnanananthan +7
During the COVID-19 pandemic, the sheer volume of imaging performed in an emergency setting for COVID-19 diagnosis has resulted in a wide variability of clinical CXR acquisitions.…
Enhancing Cancer Prediction in Challenging Screen-Detected Incident Lung Nodules Using Time-Series Deep Learning
Shahab Aslani, Pavan Alluri, Eyjolfur Gudmundsson +10
Lung cancer is the leading cause of cancer-related mortality worldwide. Lung cancer screening (LCS) using annual low-dose computed tomography (CT) scanning has been proven to signi…
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI
Shahab Aslani, Vittorio Murino, Michael Dayan +3
This paper presents a simple and effective generalization method for magnetic resonance imaging (MRI) segmentation when data is collected from multiple MRI scanning sites and as a…
Multi-branch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation
Shahab Aslani, Michael Dayan, Loredana Storelli +4
In this paper, we present an automated approach for segmenting multiple sclerosis (MS) lesions from multi-modal brain magnetic resonance images. Our method is based on a deep end-t…