2 citations · 4 across the 19 of their papers we have counts for
5 papers · 1 filter
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…
HASD: Hierarchical Adaption for pathology Slide-level Domain-shift
Jingsong Liu, Han Li, Chen Yang +6
Domain shift is a critical problem for pathology AI as pathology data is heavily influenced by center-specific conditions. Current pathology domain adaptation methods focus on imag…