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20182025
most citedDeep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation

41 citations · 63 across the 17 of their papers we have counts for

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7 papers · 1 filter

physics.med-ph2025

Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CT: From Simulated to Real Data

Nikita Moriakov, Efstratios Gavves, Jonathan H. Mason +3

Cone Beam CT (CBCT) is an important imaging modality nowadays, however lower image quality of CBCT compared to more conventional Computed Tomography (CT) remains a limiting factor…

physics.med-ph2024

Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CT

Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

Cone Beam CT (CBCT) is an essential imaging modality nowadays, but the image quality of CBCT still lags behind the high quality standards established by the conventional Computed T…

physics.med-ph2023

Improving Lesion Volume Measurements on Digital Mammograms

Nikita Moriakov, Jim Peters, Ritse Mann +4

Lesion volume is an important predictor for prognosis in breast cancer. We make a step towards a more accurate lesion volume measurement on digital mammograms by developing a model…

physics.med-ph2022★ 9 cited

End-to-end Memory-Efficient Reconstruction for Cone Beam CT

Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

Cone Beam CT plays an important role in many medical fields nowadays, but the potential of this imaging modality is hampered by lower image quality compared to the conventional CT.…

physics.med-ph2020★ 1 cited

Deep Learning-based Initialization of Iterative Reconstruction for Breast Tomosynthesis

Koen Michielsen, Nikita Moriakov, Jonas Teuwen +1

Reconstruction of digital breast tomosynthesis is a challenging problem due to the limited angle data available in such systems. Due to memory limitations, deep learning-based meth…

physics.med-ph2020★ 41 cited

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation

Jonas Teuwen, Nikita Moriakov, Christian Fedon +7

The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital…

physics.med-ph2018★ 1 cited

Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction

Nikita Moriakov, Koen Michielsen, Jonas Adler +3

Digital breast tomosynthesis is rapidly replacing digital mammography as the basic x-ray technique for evaluation of the breasts. However, the sparse sampling and limited angular r…