Sepehr Jalali

M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Real-World Applications

Tim Laibacher, Tillman Weyde, Sepehr Jalali · 2019 · 111 citations

Convolutional Neural Network, High Resolution Images, Machine Learning +24

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

Humayun Irshad, Sepehr Jalali, Ludovic Roux et al. · Journal of Pathology Informatics · 2013 · 98 citations · Full text

Deep iterative vessel segmentation in OCT angiography

Theodoros Pissas, Edward Bloch, M. Jorge Cardoso et al. · Biomedical Optics Express · 2020 · 36 citations · Full text

M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Resource-Constrained Environments

Tim Laibacher, Tillman Weyde, Sepehr Jalali · arXiv (Cornell University) · 2018 · 28 citations · Full text

Convolutional Neural Network, High Resolution Images, Machine Learning +24

Learned optical flow for intra-operative tracking of the retinal fundus

Claudio S. Ravasio, Theodoros Pissas, Edward Bloch et al. · International Journal of Computer Assisted Radiology and Surgery · 2020 · 10 citations · Full text