most citedA deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography

44 citations

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eess.IV2022★ 44 cited

A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography

Roy Schwartz, Hagar Khalid, Sandra Liakopoulos +12

Purpose - To develop and validate a deep learning (DL) framework for the detection and quantification of drusen and reticular pseudodrusen (RPD) on optical coherence tomography sca…

eess.IV2022★ 38 cited

A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation

Lucas Fidon, Michael Aertsen, Florian Kofler +18

Deep learning models for medical image segmentation can fail unexpectedly and spectacularly for pathological cases and images acquired at different centers than training images, wi…

eess.IV2021★ 33 cited

Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

Lucas Fidon, Michael Aertsen, Doaa Emam +9

Deep neural networks have increased the accuracy of automatic segmentation, however, their accuracy depends on the availability of a large number of fully segmented images. Methods…