101 citations · 204 across the 16 of their papers we have counts for
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MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis
Michael Gadermayr, Lukas Koller, Maximilian Tschuchnig +5
Multiple instance learning exhibits a powerful approach for whole slide image-based diagnosis in the absence of pixel- or patch-level annotations. In spite of the huge size of hole…
Multiple Instance Learning for Digital Pathology: A Review on the State-of-the-Art, Limitations & Future Potential
Michael Gadermayr, Maximilian Tschuchnig
Digital whole slides images contain an enormous amount of information providing a strong motivation for the development of automated image analysis tools. Particularly deep neural…
Evaluation of Multi-Scale Multiple Instance Learning to Improve Thyroid Cancer Classification
Maximilian E. Tschuchnig, Philipp Grubmüller, Lea M. Stangassinger +5
Thyroid cancer is currently the fifth most common malignancy diagnosed in women. Since differentiation of cancer sub-types is important for treatment and current, manual methods ar…