6 citations · 7 across the 3 of their papers we have counts for
4 papers
Domain Adaptation using Silver Standard Labels for Ki-67 Scoring in Digital Pathology: A Step Closer to Widescale Deployment
Amanda Dy, Ngoc-Nhu Jennifer Nguyen, Seyed Hossein Mirjahanmardi +7
Deep learning systems have been proposed to improve the objectivity and efficiency of Ki- 67 PI scoring. The challenge is that while very accurate, deep learning techniques suffer…
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…