1.3k citations · 7.9k across the 178 of their papers we have counts for
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Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
Suprosanna Shit, Abinav Ravi Venkatakrishnan, Ivan Ezhov +3
Fast and accurate solution of time-dependent partial differential equations (PDEs) is of key interest in many research fields including physics, engineering, and biology. Generally…
ModelHub.AI: Dissemination Platform for Deep Learning Models
Ahmed Hosny, Michael Schwier, Christoph Berger +13
Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among…
Adversarial Convolutional Networks with Weak Domain-Transfer for Multi-Sequence Cardiac MR Images Segmentation
Jingkun Chen, Hongwei Li, Jianguo Zhang +1
Analysis and modeling of the ventricles and myocardium are important in the diagnostic and treatment of heart diseases. Manual delineation of those tissues in cardiac MR (CMR) scan…
Shape-Aware Complementary-Task Learning for Multi-Organ Segmentation
Fernando Navarro, Suprosanna Shit, Ivan Ezhov +5
Multi-organ segmentation in whole-body computed tomography (CT) is a constant pre-processing step which finds its application in organ-specific image retrieval, radiotherapy planni…
Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis
Anjany Sekuboyina, Markus Rempfler, Alexander Valentinitsch +3
We propose an auto-encoding network architecture for point clouds (PC) capable of extracting shape signatures without supervision. Building on this, we (i) design a loss function c…
Asymmetric Cascade Networks for Focal Bone Lesion Prediction in Multiple Myeloma
Roxane Licandro, Johannes Hofmanninger, Matthias Perkonigg +7
The reliable and timely stratification of bone lesion evolution risk in smoldering Multiple Myeloma plays an important role in identifying prime markers of the disease's advance an…
Neural parameters estimation for brain tumor growth modeling
Ivan Ezhov, Jana Lipkova, Suprosanna Shit +5
Understanding the dynamics of brain tumor progression is essential for optimal treatment planning. Cast in a mathematical formulation, it is typically viewed as evaluation of a sys…
Cross-view Relation Networks for Mammogram Mass Detection
Jiechao Ma, Sen Liang, Xiang Li +4
Mammogram is the most effective imaging modality for the mass lesion detection of breast cancer at the early stage. The information from the two paired views (i.e., medio-lateral o…
DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis
Hongwei Li, Johannes C. Paetzold, Anjany Sekuboyina +5
Synthesizing MR imaging sequences is highly relevant in clinical practice, as single sequences are often missing or are of poor quality (e.g. due to motion). Naturally, the idea ar…
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Amber L. Simpson, Michela Antonelli, Spyridon Bakas +21
Semantic segmentation of medical images aims to associate a pixel with a label in a medical image without human initialization. The success of semantic segmentation algorithms is c…
Labelling Vertebrae with 2D Reformations of Multidetector CT Images: An Adversarial Approach for Incorporating Prior Knowledge of Spine Anatomy
Anjany Sekuboyina, Markus Rempfler, Alexander Valentinitsch +2
Purpose: To use and test a labelling algorithm that operates on two-dimensional (2D) reformations, rather than three-dimensional (3D) data to locate and identify vertebrae. Methods…
Designing contrasts for rapid, simultaneous parameter quantification and flow visualization with quantitative transient-state imaging
Pedro A. Gómez, Miguel Molina-Romero, Guido Buonincontri +2
Magnetic resonance imaging (MRI) is a remarkably powerful diagnostic technique: it generates wide-ranging information for the non-invasive study of tissue anatomy and physiology. C…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…