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Article
Open AccessFundamentals of Arthroscopic Surgery Training and beyond: a reinforcement learning exploration and benchmark
This work presents FASTRL, a benchmark set of instrument manipulation tasks adapted to the domain of reinforcement learning and used in simulated surgical training. This benchmark enables and supports the design ...
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Article
Open AccessSelf-supervised representation learning for surgical activity recognition
Purpose: Virtual reality-based simulators have the potential to become an essential part of surgical education. To make full use of this potential, they must be able to automatically recognize activities performe...
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Article
Open AccessEntrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography
White matter tractography, based on diffusion-weighted magnetic resonance images, is currently the only available in vivo method to gather information on the structural brain connectivity. The low resolution o...
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Chapter and Conference Paper
Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization
Mitral valve segmentation specifies a crucial first step to establi...
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Chapter and Conference Paper
Entrack: A Data-Driven Maximum-Entropy Approach to Fiber Tractography
The combined effort of brain anatomy experts and computerized methods has continuously improved the quality of available gold-standard tractograms for diffusion-weighted MRI. These prototypical tractograms co...
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Chapter and Conference Paper
Generative Aging of Brain MR-Images and Prediction of Alzheimer Progression
Predicting the age progression of individual brain images from longitudinal data has been a challenging problem, while its solution is considered key to improve dementia prognosis. Often, approaches are limit...
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Chapter and Conference Paper
MRI-Based Surgical Planning for Lumbar Spinal Stenosis
The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis (LSS). For LSS, treatment decisions based on clinical and radiological information as well as personal experience of the ...
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Chapter and Conference Paper
Model Selection for Gaussian Process Regression
Gaussian processes are powerful tools since they can model non-linear dependencies between inputs, while remaining analytically tractable. A Gaussian process is characterized by a mean function and a covarianc...
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Chapter
SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data
In biological imaging the data is often represented by a sequence of anisotropic frames — the resolution in one dimension is significantly lower than in the other dimensions. E.g. in electron microscopy it ari...
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Article
Open AccessImage-based computational quantification and visualization of genetic alterations and tumour heterogeneity
Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and hist...
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Article
Open AccessAsymptotic analysis of estimators on multi-label data
Multi-label classification extends the standard multi-class classification paradigm by drop** the assumption that classes have to be mutually exclusive, i.e., the same data item might belong to more than one...
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Chapter and Conference Paper
Visual Saliency Based Active Learning for Prostate MRI Segmentation
We propose an active learning (AL) approach for prostate segmentation from magnetic resonance (MR) images. Our label query strategy is inspired from the principles of visual saliency that has similar considera...
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Chapter and Conference Paper
Boosting Convolutional Filters with Entropy Sampling for Optic Cup and Disc Image Segmentation from Fundus Images
We propose a novel convolutional neural network (CNN) based method for optic cup and disc segmentation. To reduce computational complexity, an entropy based sampling technique is introduced that gives superior...
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Article
Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry
This paper reports the use of mass cytometry on adherent cells and tissue samples for highly multiplexed imaging at subcellular resolution.
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Chapter and Conference Paper
Convolutional Decision Trees for Feature Learning and Segmentation
Most computer vision and especially segmentation tasks require to extract features that represent local appearance of patches. Relevant features can be further processed by learning algorithms to infer posteri...
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Chapter and Conference Paper
Semi-automatic Crohn’s Disease Severity Estimation on MR Imaging
Crohn’s disease (CD) is a chronic inflammatory bowel disease which can be visualized by magnetic resonance imaging (MRI). For CD grading, several non-invasive MRI based severity scores are known, most prominen...
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Chapter and Conference Paper
Combining Multiple Expert Annotations Using Semi-supervised Learning and Graph Cuts for Crohn’s Disease Segmentation
We propose a graph cut (GC) based approach for combining annotations from multiple experts and segmenting Crohns disease (CD) tissues in magnetic resonance (MR) images. Random forest (RF) based semi supervised...
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Chapter
Computational Design of Informative Experiments in Systems Biology
Accurate predictions of the behavior of biological systems can be achieved through multiple iterations of modeling and experimentation. In this chapter, we present the central ideas for the design of informati...
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Article
A Supervised Learning Approach for Crohn's Disease Detection Using Higher-Order Image Statistics and a Novel Shape Asymmetry Measure
Increasing incidence of Crohn’s disease (CD) in the Western world has made its accurate diagnosis an important medical challenge. The current reference standard for diagnosis, colonoscopy, is time-consuming an...
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Chapter and Conference Paper
A Model Development Pipeline for Crohn’s Disease Severity Assessment from Magnetic Resonance Images
Crohn’s Disease affects the intestinal tract of a patient and can have varying severity which influences treatment strategy. The clinical severity score CDEIS (Crohn’s Disease Endoscopic Index of severity) ran...
