189 citations · 196 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
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…