Yucca: A deep learning framework for medical image analysis

SN Llambias, J Machnio, A Munk, J Ambsdorf… - arXiv preprint arXiv …, 2024 - arxiv.org
Medical image analysis using deep learning frameworks has advanced healthcare by
automating complex tasks, but many existing frameworks lack flexibility, modularity, and user …

[HTML][HTML] Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges

M Ferlin, Z Klawikowska, M Grochowski… - Expert Systems with …, 2023 - Elsevier
This paper provides the first review to date which gathers, describes, and assesses, to the
best of our knowledge, all available publications on automating cerebral microbleed (CMB) …

Data Augmentation-Based Unsupervised Domain Adaptation In Medical Imaging

SN Llambias, M Nielsen, MM Ghazi - arXiv preprint arXiv:2308.04395, 2023 - arxiv.org
Deep learning-based models in medical imaging often struggle to generalize effectively to
new scans due to data heterogeneity arising from differences in hardware, acquisition …

COVID-19-associated cerebral microbleeds in the general population

MV Sagar, NR Ferrer, M Mehdipour Ghazi… - Brain …, 2024 - academic.oup.com
Cerebral microbleeds are frequent incidental findings on brain MRI and have previously
been shown to occur in Coronavirus Disease 2019 (COVID-19) cohorts of critically ill …

Heterogeneous Learning for Brain Lesion Segmentation, Detection, and Classification

SN Llambias, M Nielsen, MM Ghazi - Northern Lights Deep …, 2024 - openreview.net
Brain lesions detected in magnetic resonance images often vary in type and rarity across
different cohorts, posing a challenge for deep learning techniques that are typically …

[PDF][PDF] BRAIN COMMUNICATIONS

MV Sagar, NR Ferrer, MM Ghazi, KV Klein… - 2024 - scienceopen.com
COVID-19-associated cerebral microbleeds in the general population Page 1 COVID-19-associated
cerebral microbleeds in the general population Malini V. Sagar,1,* Neus R. Ferrer,2,* Mostafa …