output
20042025
most citedCompressed sensing for longitudinal MRI: An adaptive-weighted approach

84 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing eess.IVShow all

5 papers · 1 filter

eess.IV2024★ 2 cited

X-ray2CTPA: Leveraging Diffusion Models to Enhance Pulmonary Embolism Classification

Noa Cahan, Eyal Klang, Galit Aviram +4

Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detai…

eess.IV2022★ 3 cited

Partial annotations for the segmentation of large structures with low annotation cost

Bella Specktor Fadida, Daphna Link Sourani, Liat Ben Sira Elka Miller +2

Deep learning methods have been shown to be effective for the automatic segmentation of structures and pathologies in medical imaging. However, they require large annotated dataset…

eess.IV2022

BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes

Netanell Avisdris, Leo Joskowicz, Brian Dromey +5

Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometr…

eess.IV2022★ 63 cited

Fetal Brain Tissue Annotation and Segmentation Challenge Results

Kelly Payette, Hongwei Li, Priscille de Dumast +55

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…

eess.IV2021★ 32 cited

Automatic linear measurements of the fetal brain on MRI with deep neural networks

Netanell Avisdris, Bossmat Yehuda, Ori Ben-Zvi +6

Timely, accurate and reliable assessment of fetal brain development is essential to reduce short and long-term risks to fetus and mother. Fetal MRI is increasingly used for fetal b…