1 citations · 1 across the 9 of their papers we have counts for
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From Cells to Survival: Hierarchical Analysis of Cell Inter-Relations in Multiplex Microscopy for Lung Cancer Prognosis
Olle Edgren Schüllerqvist, Jens Baumann, Joakim Lindblad +4
The tumor microenvironment (TME) has emerged as a promising source of prognostic biomarkers. To fully leverage its potential, analysis methods must capture complex interactions bet…
SLAM-AGS: Slide-Label Aware Multi-Task Pretraining Using Adaptive Gradient Surgery in Computational Cytology
Marco Acerbis, Swarnadip Chatterjee, Christophe Avenel +1
Computational cytology faces two major challenges: i) instance-level labels are unreliable and prohibitively costly to obtain, ii) witness rates are extremely low. We propose SLAM-…
Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…
A Comparison of Deep Learning Methods for Cell Detection in Digital Cytology
Marco Acerbis, Nataša Sladoje, Joakim Lindblad
Accurate and efficient cell detection is crucial in many biomedical image analysis tasks. We evaluate the performance of several Deep Learning (DL) methods for cell detection in Pa…
Isolated Channel Vision Transformers: From Single-Channel Pretraining to Multi-Channel Finetuning
Wenyi Lian, Patrick Micke, Joakim Lindblad +1
Vision Transformers (ViTs) have achieved remarkable success in standard RGB image processing tasks. However, applying ViTs to multi-channel imaging (MCI) data, e.g., for medical an…