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20202023
most citedHigh-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection

34 citations · 48 across the 7 of their papers we have counts for

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4 papers · 1 filter

eess.IV2023★ 4 cited

RADIFUSION: A multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement

Hong Hui Yeoh, Andrea Liew, Raphaël Phan +5

Breast cancer is a significant public health concern and early detection is critical for triaging high risk patients. Sequential screening mammograms can provide important spatiote…

eess.IV2022★ 34 cited

High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection

Lidia Garrucho, Kaisar Kushibar, Richard Osuala +7

Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance sinc…

eess.IV2021★ 1 cited

Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT

Simone Bendazzoli, Irene Brusini, Mehdi Astaraki +7

Segmentation of COVID-19 lesions from chest CT scans is of great importance for better diagnosing the disease and investigating its extent. However, manual segmentation can be very…

eess.IV2020★ 2 cited

Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models

Yue Liu, Hossein Azizpour, Fredrik Strand +1

The ability to accurately estimate risk of developing breast cancer would be invaluable for clinical decision-making. One promising new approach is to integrate image-based risk mo…