309 citations · 501 across the 11 of their papers we have counts for
5 papers · 1 filter
Preserving Dense Features for Ki67 Nuclei Detection
Seyed Hossein Mirjahanmardi, Melanie Dawe, Anthony Fyles +4
Nuclei detection is a key task in Ki67 proliferation index estimation in breast cancer images. Deep learning algorithms have shown strong potential in nuclei detection tasks. Howev…
Mitosis Detection for Breast Cancer Pathology Images Using UV-Net
Seyed H. Mirjahanmardi, Samir Mitha, Salar Razavi +2
The difficulty of detecting mitosis and its similarity to non-mitosis objects has remained a challenge in computational pathology. The lack of publicly available data has added mor…
Cascade RCNN for MIDOG Challenge
Salar Razavi, Fariba Dambandkhameneh, Dimitri Androutsos +2
Mitotic counts are one of the key indicators of breast cancer prognosis. However, accurate mitotic cell counting is still a difficult problem and is labourious. Automated methods h…
Adapting to Unseen Vendor Domains for MRI Lesion Segmentation
Brandon Mac, Alan R. Moody, April Khademi
One of the key limitations in machine learning models is poor performance on data that is out of the domain of the training distribution. This is especially true for image analysis…
FlowReg: Fast Deformable Unsupervised Medical Image Registration using Optical Flow
Sergiu Mocanu, Alan R. Moody, April Khademi
We propose FlowReg, a deep learning-based framework for unsupervised image registration for neuroimaging applications. The system is composed of two architectures that are trained…