1 citations · 1 across the 4 of their papers we have counts for
4 papers
BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling
Ali Keshavarzi, Quentin Bouniot, Benjamin M. Smith +1
Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understanding various respiratory di…
Boundary-Emphasized Weight Maps for Distal Airway Segmentation
Ali Keshavarzi, Elsa Angelini
Automated airway segmentation from lung CT scans is vital for diagnosing and monitoring pulmonary diseases. Despite advancements, challenges like leakage, breakage, and class imbal…
Curriculum Learning for Few-Shot Domain Adaptation in CT-based Airway Tree Segmentation
Maxime Jacovella, Ali Keshavarzi, Elsa Angelini
Despite advances with deep learning (DL), automated airway segmentation from chest CT scans continues to face challenges in segmentation quality and generalization across cohorts.…
Few-Shot Airway-Tree Modeling using Data-Driven Sparse Priors
Ali Keshavarzi, Elsa Angelini
The lack of large annotated datasets in medical imaging is an intrinsic burden for supervised Deep Learning (DL) segmentation models. Few-shot learning approaches are cost-effectiv…