331 citations
- KTH Royal Institute of TechnologySE8 papers
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4 papers · 1 filter
Targeted Iterative Filtering
Freddie Åström, Michael Felsberg, George Baravdish +1
The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different…
Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance
Milda Pocevičiūtė, Gabriel Eilertsen, Stina Garvin +1
Multiple-instance learning (MIL) is an attractive approach for digital pathology applications as it reduces the costs related to data collection and labelling. However, it is not c…
Survey of XAI in digital pathology
Milda Pocevičiūtė, Gabriel Eilertsen, Claes Lundström
Artificial intelligence (AI) has shown great promise for diagnostic imaging assessments. However, the application of AI to support medical diagnostics in clinical routine comes wit…
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
Mitko Veta, Yujing J. Heng, Nikolas Stathonikos +30
Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is highly subjective an…