4 papers
Certainty Pooling for Multiple Instance Learning
Jacob Gildenblat, Ido Ben-Shaul, Zvi Lapp +1
Multiple Instance Learning is a form of weakly supervised learning in which the data is arranged in sets of instances called bags with one label assigned per bag. The bag level cla…
Self-Supervised Similarity Learning for Digital Pathology
Jacob Gildenblat, Eldad Klaiman
Using features extracted from networks pretrained on ImageNet is a common practice in applications of deep learning for digital pathology. However it presents the downside of missi…
Virtualization of tissue staining in digital pathology using an unsupervised deep learning approach
Amal Lahiani, Jacob Gildenblat, Irina Klaman +3
Histopathological evaluation of tissue samples is a key practice in patient diagnosis and drug development, especially in oncology. Historically, Hematoxylin and Eosin (H&E) has be…
Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks
Amal Lahiani, Jacob Gildenblat, Irina Klaman +2
A key challenge in cancer immunotherapy biomarker research is quantification of pattern changes in microscopic whole slide images of tumor biopsies. Different cell types tend to mi…