5 citations · 8 across the 3 of their papers we have counts for
3 papers
eess.IV2024
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…
eess.IV2024★ 5 cited
Pre-examinations Improve Automated Metastases Detection on Cranial MRI
Katerina Deike-Hofmann, Dorottya Dancs, Daniel Paech +5
Materials and methods: First, a dual-time approach was assessed, for which the CNN was provided sequences of the MRI that initially depicted new MM (diagnosis MRI) as well as of a…
eess.IV2024★ 3 cited
Gadolinium dose reduction for brain MRI using conditional deep learning
Thomas Pinetz, Erich Kobler, Robert Haase +7
Recently, deep learning (DL)-based methods have been proposed for the computational reduction of gadolinium-based contrast agents (GBCAs) to mitigate adverse side effects while pre…