Publications by authors named "Weronika Celniak"
Artifact Augmentation for Learning-based Quality Control of Whole Slide Images.
Annu Int Conf IEEE Eng Med Biol Soc
July 2023
The acquisition of whole slide images is prone to artifacts that can require human control and re-scanning, both in clinical workflows and in research-oriented settings. Quality control algorithms are a first step to overcome this challenge, as they limit the use of low quality images. Developing quality control systems in histopathology is not straightforward, also due to the limited availability of data related to this topic.
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- The analysis of veterinary radiographic imaging data is crucial for diagnosing thoracic lesions but is time-consuming for physicians; an automated system could streamline this process.
- Most current systems rely on supervised deep learning, which requires extensive labeled data that is often hard to obtain due to high costs and time commitments.
- This study introduces a novel approach using self-supervised learning techniques on publicly available unlabeled radiographic data to enhance classification accuracy, achieving mean ROC AUC scores of 0.77 and 0.66 in laterolateral and dorsoventral projections, respectively.