Benjamin Risse
YOU?
Author Swipe
View article: WildDrone: autonomous drone technology for monitoring wildlife populations
WildDrone: autonomous drone technology for monitoring wildlife populations Open
The rapid loss of biodiversity worldwide is unprecedented, with more species facing extinction now than at any other time in human history. Key factors contributing to this decline include habitat destruction, overexploitation, and climate…
View article: MARTHA - Combining gaze into deep learning for fully quantitative human testicular histology analysis
MARTHA - Combining gaze into deep learning for fully quantitative human testicular histology analysis Open
Despite advances in computational pathology, manual tissue examinations remain the gold standard in diagnostics, resulting in thousands of whole slide image inspections in daily practice. Unfortunately, examination strategies and identifie…
View article: OR27-04 Unraveling the Genetic Architecture of Male Fertility: A Population-Based GWAS of Testicular Volume Using Machine Learning-Based Segmentation
OR27-04 Unraveling the Genetic Architecture of Male Fertility: A Population-Based GWAS of Testicular Volume Using Machine Learning-Based Segmentation Open
Disclosure: P. Beeken: None. J. Ernsting: None. L. Ogoniak: None. J. Kockwelp: None. T. Hahn: None. B. Risse: None. A.S. Busch: None. Background: The genetic factors influencing male fertility remain elusive. While testicular volume closel…
View article: Towards population scale testis volume segmentation in DIXON MRI
Towards population scale testis volume segmentation in DIXON MRI Open
Testis size is known to be one of the main predictors of male fertility, usually assessed in clinical workup via palpation or imaging. Despite its potential, population-level evaluation of testicular volume using imaging remains underexplo…
View article: Hatching-Box: Automated in situ monitoring of Drosophila melanogaster development in standard rearing vials
Hatching-Box: Automated in situ monitoring of Drosophila melanogaster development in standard rearing vials Open
In this paper we propose the Hatching-Box, a novel in situ imaging and analysis system to automatically monitor and quantify the developmental behavior of Drosophila melanogaster in standard rearing vials and during regular rearing routine…
View article: Rethinking interaction design - special implications for interaction concepts in medical education using virtual reality
Rethinking interaction design - special implications for interaction concepts in medical education using virtual reality Open
This study investigates the impact of hand representation in virtual reality based medical education on user behaviour, with a particular focus on medical teaching objectives and navigation within the scenario. In VR it is common to adapt …
View article: Teach the Unteachable with a Virtual Reality (VR) Brain Death Scenario – 800 Students and 3 Years of Experience
Teach the Unteachable with a Virtual Reality (VR) Brain Death Scenario – 800 Students and 3 Years of Experience Open
Introduction: Traditionally, clinical education has combined classroom theory with hospital-based practical experiences. Over the past 50 years, simulation-based training, particularly virtual reality (VR), has gained prominence for its fl…
View article: pyAKI—An open source solution to automated acute kidney injury classification
pyAKI—An open source solution to automated acute kidney injury classification Open
Objective Acute kidney injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improvin…
View article: S-ROPE: Spectral Frame Representation of Periodic Events
S-ROPE: Spectral Frame Representation of Periodic Events Open
In this paper we introduce a novel event surface representation designed for encoding temporal information of dynamic vision sensors (DVS) into a multi-channel frame format. Different representations have been proposed to extract features …
View article: Learned Random Label Predictions as a Neural Network Complexity Metric
Learned Random Label Predictions as a Neural Network Complexity Metric Open
We empirically investigate the impact of learning randomly generated labels in parallel to class labels in supervised learning on memorization, model complexity, and generalization in deep neural networks. To this end, we introduce a multi…
View article: The Hatching-Box: A Novel System for Automated Monitoring and Quantification of Drosophila melanogaster Developmental Behavior
The Hatching-Box: A Novel System for Automated Monitoring and Quantification of Drosophila melanogaster Developmental Behavior Open
In this paper we propose the Hatching-Box, a novel imaging and analysis system to automatically monitor and quantify the developmental behavior of Drosophila in standard rearing vials and during regular rearing routines, rendering explicit…
View article: Compensation to visual impairments and behavioral plasticity in navigating ants
Compensation to visual impairments and behavioral plasticity in navigating ants Open
Desert ants are known to rely heavily on vision while venturing for food and returning to the nest. During these foraging trips, ants memorize and recognize their visual surroundings, which enables them to recapitulate individually learned…
View article: Towards Population Scale Testis Volume Segmentation in DIXON MRI
Towards Population Scale Testis Volume Segmentation in DIXON MRI Open
Testis size is known to be one of the main predictors of male fertility, usually assessed in clinical workup via palpation or imaging. Despite its potential, population-level evaluation of testicular volume using imaging remains underexplo…
View article: deepmriprep: Voxel-based Morphometry (VBM) Preprocessing via Deep Neural Networks
deepmriprep: Voxel-based Morphometry (VBM) Preprocessing via Deep Neural Networks Open
Voxel-based Morphometry (VBM) has emerged as a powerful approach in neuroimaging research, utilized in over 7,000 studies since the year 2000. Using Magnetic Resonance Imaging (MRI) data, VBM assesses variations in the local density of bra…
View article: Probabilistic Photonic Computing with Chaotic Light
Probabilistic Photonic Computing with Chaotic Light Open
Biological neural networks effortlessly tackle complex computational problems and excel at predicting outcomes from noisy, incomplete data, a task that poses significant challenges to traditional processors. Artificial neural networks (ANN…
View article: Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches
Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches Open
Graph neural networks (GNNs) are a natural choice to represent chemical data, due to their inherent ability to handle arbitrary input topologies. They avoid the need to convert molecules into molecular fingerprints with a fixed vector leng…
View article: VR-based Competence Training at Scale: Teaching Clinical Skills in the Context of Virtual Brain Death Examination
VR-based Competence Training at Scale: Teaching Clinical Skills in the Context of Virtual Brain Death Examination Open
Teaching medical practical and soft skills in clinical routines is increasingly difficult, and manikin or actor-based simulations have gained popularity in the last decades. These simulations, however, hardly scale with the demand, are com…
View article: Towards Estimation of 3D Poses and Shapes of Animals from Oblique Drone Imagery
Towards Estimation of 3D Poses and Shapes of Animals from Oblique Drone Imagery Open
Wildlife research in both terrestrial and aquatic ecosystems now deploys drone technology for tasks such as monitoring, census counts and habitat analysis. Unlike camera traps, drones offer real-time flexibility for adaptable flight paths …
View article: OccFlowNet: Towards Self-supervised Occupancy Estimation via Differentiable Rendering and Occupancy Flow
OccFlowNet: Towards Self-supervised Occupancy Estimation via Differentiable Rendering and Occupancy Flow Open
Semantic occupancy has recently gained significant traction as a prominent 3D scene representation. However, most existing methods rely on large and costly datasets with fine-grained 3D voxel labels for training, which limits their practic…
View article: Accelerating finite-difference frequency-domain simulations of inverse designed structures in nanophotonics using deep learning
Accelerating finite-difference frequency-domain simulations of inverse designed structures in nanophotonics using deep learning Open
The inverse design of nanophotonic devices is becoming increasingly relevant for the development of complex photonic integrated circuits. Electromagnetic first-order simulations contribute to the overwhelming computational cost of the opti…
View article: Probabilistic Photonic Computing with Chaotic Light
Probabilistic Photonic Computing with Chaotic Light Open
Biological neural networks effortlessly tackle complex computational problems and excel at predicting outcomes from noisy, incomplete data, a task that poses significant challenges to traditional processors. Artificial neural networks (ANN…
Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep learning-based feature extraction Open
Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a pr…
View article: pyAKI -- An Open Source Solution to Automated KDIGO classification
pyAKI -- An Open Source Solution to Automated KDIGO classification Open
Acute Kidney Injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improving Global O…
View article: Momentum-SAM: Sharpness Aware Minimization without Computational Overhead
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead Open
The recently proposed optimization algorithm for deep neural networks Sharpness Aware Minimization (SAM) suggests perturbing parameters before gradient calculation by a gradient ascent step to guide the optimization into parameter space re…
View article: A Systematic Evaluation of Machine Learning–Based Biomarkers for Major Depressive Disorder
A Systematic Evaluation of Machine Learning–Based Biomarkers for Major Depressive Disorder Open
Importance Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative bioma…