1 code implementation • 27 Sep 2023 • Roshan Prakash Rane, Jihoon Kim, Arjun Umesha, Didem Stark, Marc-André Schulz, Kerstin Ritter
In conclusion, the DeepRepViz framework provides a systematic approach to test for potential confounders such as age, sex, and imaging artifacts and improves the transparency of DL models for neuroimaging studies.
no code implementations • 20 Jan 2023 • Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter
By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks have advanced to a powerful tool in medical imaging.