7 papers
Re-mixing Embeddings for Patient Augmentation in Data Scarce Multiple Instance Learning
Muhammed Furkan Dasdelen, Fatih Ozlugedik, Anastasia Litinetskaya +3
Data scarcity is a major bottleneck in medical Multiple Instance Learning (MIL), especially for rare diseases or expensive modalities. We introduce a statistically grounded patient…
Measuring Prediction Uncertainty in Neural Cellular Automata
Ario Sadafi, Michael Deutges, Nassir Navab +1
Neural cellular automata (NCA) provide a lightweight alternative to encoder-decoder segmentation networks. However, it can be difficult to decide when a prediction should be truste…
Transformer-Based Hematological Malignancy Prediction from Peripheral Blood Smears in a Real-World Cohort
Muhammed Furkan Dasdelen, Ivan Kukuljan, Peter Lienemann +6
Peripheral blood smears remain a cornerstone in the diagnosis of hematological neoplasms, offering rapid and valuable insights that inform subsequent diagnostic steps. However, sin…
Attention Pooling Enhances NCA-based Classification of Microscopy Images
Chen Yang, Michael Deutges, Jingsong Liu +4
Neural Cellular Automata (NCA) offer a robust and interpretable approach to image classification, making them a promising choice for microscopy image analysis. However, a performan…
Neural Cellular Automata for Weakly Supervised Segmentation of White Blood Cells
Michael Deutges, Chen Yang, Raheleh Salehi +3
The detection and segmentation of white blood cells in blood smear images is a key step in medical diagnostics, supporting various downstream tasks such as automated blood cell cou…
Continual Multiple Instance Learning for Hematologic Disease Diagnosis
Zahra Ebrahimi, Raheleh Salehi, Nassir Navab +2
The dynamic environment of laboratories and clinics, with streams of data arriving on a daily basis, requires regular updates of trained machine learning models for consistent perf…