2 code implementations • 6 Jun 2023 • Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar
Fourier Neural Operators (FNOs) have proven to be an efficient and effective method for resolution-independent operator learning in a broad variety of application areas across scientific machine learning.
no code implementations • 18 Mar 2020 • Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett Landman, Klaus Maier-Hein, Sebastien Ourselin, Micah Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso
Data-driven Machine Learning has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems.
no code implementations • 2 Oct 2019 • Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M. Jorge Cardoso, Andrew Feng
Due to medical data privacy regulations, it is often infeasible to collect and share patient data in a centralised data lake.
no code implementations • 5 Nov 2018 • Rüdiger Göbl, Diana Mateus, Christoph Hennersperger, Maximilian Baust, Nassir Navab
By providing a novel paradigm for the acquisition and reconstruction of tracked freehand 3D ultrasound, this work presents the concept of Computational Sonography (CS) to model the directionality of ultrasound information.
no code implementations • 13 Aug 2018 • Guilherme Aresta, Teresa Araújo, Scotty Kwok, Sai Saketh Chennamsetty, Mohammed Safwan, Varghese Alex, Bahram Marami, Marcel Prastawa, Monica Chan, Michael Donovan, Gerardo Fernandez, Jack Zeineh, Matthias Kohl, Christoph Walz, Florian Ludwig, Stefan Braunewell, Maximilian Baust, Quoc Dang Vu, Minh Nguyen Nhat To, Eal Kim, Jin Tae Kwak, Sameh Galal, Veronica Sanchez-Freire, Nadia Brancati, Maria Frucci, Daniel Riccio, Yaqi Wang, Lingling Sun, Kaiqiang Ma, Jiannan Fang, Ismael Kone, Lahsen Boulmane, Aurélio Campilho, Catarina Eloy, António Polónia, Paulo Aguiar
From the submitted algorithms it was possible to push forward the state-of-the-art in terms of accuracy (87%) in automatic classification of breast cancer with histopathological images.
no code implementations • 12 Jun 2018 • Julia Rackerseder, Maximilian Baust, Rüdiger Göbl, Nassir Navab, Christoph Hennersperger
Registration of partial-view 3D US volumes with MRI data is influenced by initialization.
1 code implementation • 4 Jun 2018 • Fausto Milletari, Nicola Rieke, Maximilian Baust, Marco Esposito, Nassir Navab
Recent neural-network-based architectures for image segmentation make extensive usage of feature forwarding mechanisms to integrate information from multiple scales.
no code implementations • CVPR 2018 • Miroslava Slavcheva, Maximilian Baust, Slobodan Ilic
We present a system that builds 3D models of non-rigidly moving surfaces from scratch in real time using a single RGB-D stream.
no code implementations • 20 Apr 2018 • Maximilian Baust, Florian Ludwig, Christian Rupprecht, Matthias Kohl, Stefan Braunewell
Variational methods for revealing visual concepts learned by convolutional neural networks have gained significant attention during the last years.
no code implementations • 9 Apr 2018 • Matthias Kohl, Christoph Walz, Florian Ludwig, Stefan Braunewell, Maximilian Baust
Breast cancer is the most frequently diagnosed cancer and leading cause of cancer-related death among females worldwide.
no code implementations • CVPR 2017 • Miroslava Slavcheva, Maximilian Baust, Daniel Cremers, Slobodan Ilic
We introduce a geometry-driven approach for real-time 3D reconstruction of deforming surfaces from a single RGB-D stream without any templates or shape priors.
no code implementations • ICCV 2017 • Christian Rupprecht, Iro Laina, Robert DiPietro, Maximilian Baust, Federico Tombari, Nassir Navab, Gregory D. Hager
In future prediction, for example, many distinct outcomes are equally valid.
no code implementations • 18 Jul 2016 • Christian Rupprecht, Elizabeth Huaroc, Maximilian Baust, Nassir Navab
We propose a method for interactive boundary extraction which combines a deep, patch-based representation with an active contour framework.
no code implementations • 23 Oct 2015 • Kanishka Sharma, Loic Peter, Christian Rupprecht, Anna Caroli, Lichao Wang, Andrea Remuzzi, Maximilian Baust, Nassir Navab
This paper presents a method for 3D segmentation of kidneys from patients with autosomal dominant polycystic kidney disease (ADPKD) and severe renal insufficiency, using computed tomography (CT) data.
no code implementations • CVPR 2015 • Maximilian Baust, Laurent Demaret, Martin Storath, Nassir Navab, Andreas Weinmann
This paper introduces the concept of shape signals, i. e., series of shapes which have a natural temporal or spatial ordering, as well as a variational formulation for the regularization of these signals.