M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Resource-Constrained Environments. - Tim Laibacher; Tillman Weyde; Sepehr Jalali (CoRR, 2018)

M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Real-World Applications. - Tim Laibacher; Tillman Weyde; Sepehr Jalali (CVPR Workshops, 2019)

On the Evaluation and Real-World Usage Scenarios of Deep Vessel Segmentation for Funduscopy. - Tim Laibacher; André Anjos (CoRR, 2019)