47 citations · 53 across the 5 of their papers we have counts for
5 papers
Correlated Feature Aggregation by Region Helps Distinguish Aggressive from Indolent Clear Cell Renal Cell Carcinoma Subtypes on CT
Karin Stacke, Indrani Bhattacharya, Justin R. Tse +3
Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Indolent RCC is often low-grade without necrosis and can be monitored without treatment. Aggressive…
Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications
Karin Stacke, Jonas Unger, Claes Lundström +1
Unsupervised learning has made substantial progress over the last few years, especially by means of contrastive self-supervised learning. The dominating dataset for benchmarking se…
Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection
Apostolia Tsirikoglou, Karin Stacke, Gabriel Eilertsen +1
The scarcity of labeled data is a major bottleneck for developing accurate and robust deep learning-based models for histopathology applications. The problem is notably prominent f…
A Study of Deep Learning Colon Cancer Detection in Limited Data Access Scenarios
Apostolia Tsirikoglou, Karin Stacke, Gabriel Eilertsen +2
Digitization of histopathology slides has led to several advances, from easy data sharing and collaborations to the development of digital diagnostic tools. Deep learning (DL) meth…
A Closer Look at Domain Shift for Deep Learning in Histopathology
Karin Stacke, Gabriel Eilertsen, Jonas Unger +1
Domain shift is a significant problem in histopathology. There can be large differences in data characteristics of whole-slide images between medical centers and scanners, making g…