14 citations · 23 across the 14 of their papers we have counts for
6 papers · 1 filter
Masked Autoencoder Pretraining and BiXLSTM ResNet Architecture for PET/CT Tumor Segmentation
Moona Mazher, Steven A Niederer, Abdul Qayyum
The accurate segmentation of lesions in whole-body PET/CT imaging is es-sential for tumor characterization, treatment planning, and response assess-ment, yet current manual workflo…
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge
Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47
The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…
Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge
Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67
Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…
Foundation Model for Whole-Heart Segmentation: Leveraging Student-Teacher Learning in Multi-Modal Medical Imaging
Abdul Qayyum, Moona Mazher, Devran Ugurlu +3
Whole-heart segmentation from CT and MRI scans is crucial for cardiovascular disease analysis, yet existing methods struggle with modality-specific biases and the need for extensiv…
Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge
Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60
Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…