713 citations · 868 across the 8 of their papers we have counts for
8 papers
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
FastSurfer-CC: A robust, accurate, and comprehensive framework for corpus callosum morphometry
Clemens Pollak, Kersten Diers, Santiago Estrada +2
The corpus callosum, the largest commissural structure in the human brain, is a central focus in research on aging and neurological diseases. It is also a critical target for inter…
FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI
Santiago Estrada, David Kügler, Emad Bahrami +5
The hypothalamus plays a crucial role in the regulation of a broad range of physiological, behavioural, and cognitive functions. However, despite its importance, only a few small-s…
Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI
Santiago Estrada, Ran Lu, Kersten Diers +5
The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic proce…
FastSurfer -- A fast and accurate deep learning based neuroimaging pipeline
Leonie Henschel, Sailesh Conjeti, Santiago Estrada +3
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands o…
FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI
Santiago Estrada, Ran Lu, Sailesh Conjeti +4
Purpose: Development of a fast and fully automated deep learning pipeline (FatSegNet) to accurately identify, segment, and quantify abdominal adipose tissue on Dixon MRI from the R…
Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks
Santiago Estrada, Sailesh Conjeti, Muneer Ahmad +2
Increased information sharing through short and long-range skip connections between layers in fully convolutional networks have demonstrated significant improvement in performance…
Complex Fully Convolutional Neural Networks for MR Image Reconstruction
Muneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada +3
Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image r…