3 papers
cs.CV2024
Leveraging image captions for selective whole slide image annotation
Jingna Qiu, Marc Aubreville, Frauke Wilm +4
Acquiring annotations for whole slide images (WSIs)-based deep learning tasks, such as creating tissue segmentation masks or detecting mitotic figures, is a laborious process due t…
eess.IV2023
Focus on Content not Noise: Improving Image Generation for Nuclei Segmentation by Suppressing Steganography in CycleGAN
Jonas Utz, Tobias Weise, Maja Schlereth +5
Annotating nuclei in microscopy images for the training of neural networks is a laborious task that requires expert knowledge and suffers from inter- and intra-rater variability, e…
cs.CV2023
Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation
Jingna Qiu, Frauke Wilm, Mathias Öttl +5
The process of annotating histological gigapixel-sized whole slide images (WSIs) at the pixel level for the purpose of training a supervised segmentation model is time-consuming. R…