Risk Classification of Brain Metastases via Radiomics, Delta-Radiomics and Machine Learning

no code implementations • 17 Feb 2023 • Philipp Sommer, Yixing Huang, Christoph Bert, Andreas Maier, Manuel Schmidt, Arnd Dörfler, Rainer Fietkau, Florian Putz

We hypothesized that using radiomics and machine learning (ML), metastases at high risk for subsequent progression could be identified during follow-up prior to the onset of significant tumor growth, enabling personalized follow-up intervals and early selection for salvage treatment.

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data

1 code implementation • 22 Dec 2021 • Yixing Huang, Christoph Bert, Philipp Sommer, Benjamin Frey, Udo Gaipl, Luitpold V. Distel, Thomas Weissmann, Michael Uder, Manuel A. Schmidt, Arnd Dörfler, Andreas Maier, Rainer Fietkau, Florian Putz

To improve brain metastasis detection performance with deep learning, a custom detection loss called volume-level sensitivity-specificity (VSS) is proposed, which rates individual metastasis detection sensitivity and specificity in (sub-)volume levels.

Ensemble Learning Specificity