Search Results for author: Andreas Maier

Found 276 papers, 59 papers with code

Deep Learning Computed Tomography based on the Defrise and Clack Algorithm

no code implementations1 Mar 2024 Chengze Ye, Linda-Sophie Schneider, Yipeng Sun, Andreas Maier

The filter is designed for a specific orbit geometry and is obtained using a data-driven approach based on deep learning.

Offline Writer Identification Using Convolutional Neural Network Activation Features

no code implementations26 Feb 2024 Vincent Christlein, David Bernecker, Andreas Maier, Elli Angelopoulou

Convolutional neural networks (CNNs) have recently become the state-of-the-art tool for large-scale image classification.

Image Classification

Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series

no code implementations29 Jan 2024 Yipeng Sun, Linda-Sophie Schneider, Fuxin Fan, Mareike Thies, Mingxuan Gu, Siyuan Mei, Yuzhong Zhou, Siming Bayer, Andreas Maier

In this study, we introduce a Fourier series-based trainable filter for computed tomography (CT) reconstruction within the filtered backprojection (FBP) framework.

Computational Efficiency Computed Tomography (CT)

Integer Optimization of CT Trajectories using a Discrete Data Completeness Formulation

no code implementations29 Jan 2024 Linda-Sophie Schneider, Gabriel Herl, Andreas Maier

X-ray computed tomography (CT) plays a key role in digitizing three-dimensional structures for a wide range of medical and industrial applications.

Computed Tomography (CT)

Two-View Topogram-Based Anatomy-Guided CT Reconstruction for Prospective Risk Minimization

no code implementations23 Jan 2024 Chang Liu, Laura Klein, Yixing Huang, Edith Baader, Michael Lell, Marc Kachelrieß, Andreas Maier

The average organ dice of the proposed method is 0. 71 compared with 0. 63 in baseline model, indicating the enhancement of anatomical structures.

Anatomy Generative Adversarial Network +3

Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification

no code implementations8 Jan 2024 Adarsh Bhandary Panambur, Hui Yu, Sheethal Bhat, Prathmesh Madhu, Siming Bayer, Andreas Maier

The assessment of breast density is crucial in the context of breast cancer screening, especially in populations with a higher percentage of dense breast tissues.

breast density classification Data Augmentation +1

Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations

no code implementations22 Dec 2023 Paul Stoewer, Achim Schilling, Andreas Maier, Patrick Krauss

Cognitive maps, as represented by the entorhinal-hippocampal complex in the brain, organize and retrieve context from memories, suggesting that large language models (LLMs) like ChatGPT could harness similar architectures to function as a high-level processing center, akin to how the hippocampus operates within the cortex hierarchy.

Hippocampus Word Embeddings

Modelling of Networked Measuring Systems -- From White-Box Models to Data Based Approaches

no code implementations21 Dec 2023 Klaus-Dieter Sommer, Peter Harris, Sascha Eichstädt, Roland Füssl, Tanja Dorst, Andreas Schütze, Michael Heizmann, Nadine Schiering, Andreas Maier, Yuhui Luo, Christos Tachtatzis, Ivan Andonovic, Gordon Gourlay

This paradigm shift holds true in particular for the digital future of measurement in all spheres of our lives and the environment, where data provided by large and complex interconnected systems of sensors are to be analysed.

SniffyArt: The Dataset of Smelling Persons

no code implementations20 Nov 2023 Mathias Zinnen, Azhar Hussian, Hang Tran, Prathmesh Madhu, Andreas Maier, Vincent Christlein

The paper also presents a baseline analysis, evaluating the performance of representative algorithms for detection, keypoint estimation, and classification tasks, showcasing the potential of combining keypoint estimation with smell gesture classification.

Classification Gesture Recognition +2

A Survey of Incremental Transfer Learning: Combining Peer-to-Peer Federated Learning and Domain Incremental Learning for Multicenter Collaboration

1 code implementation29 Sep 2023 Yixing Huang, Christoph Bert, Ahmed Gomaa, Rainer Fietkau, Andreas Maier, Florian Putz

Incremental transfer learning, which combines peer-to-peer federated learning and domain incremental learning, can overcome the data privacy issue and meanwhile preserve model performance by using continual learning techniques.

Continual Learning Federated Learning +2

Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings

no code implementations4 Jul 2023 Paul Stoewer, Achim Schilling, Andreas Maier, Patrick Krauss

The human brain possesses the extraordinary capability to contextualize the information it receives from our environment.

Word Embeddings

A Vessel-Segmentation-Based CycleGAN for Unpaired Multi-modal Retinal Image Synthesis

no code implementations5 Jun 2023 Aline Sindel, Andreas Maier, Vincent Christlein

Unpaired image-to-image translation of retinal images can efficiently increase the training dataset for deep-learning-based multi-modal retinal registration methods.

Image Registration Image-to-Image Translation +2

Deep Multi-Frame Filtering for Hearing Aids

1 code implementation14 May 2023 Hendrik Schröter, Tobias Rosenkranz, Alberto N. Escalante-B., Andreas Maier

Alternatively, the complex filter can be estimated via an MF minimum variance distortionless response (MVDR), or MF Wiener filter (WF).

Speech Enhancement

DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

1 code implementation14 May 2023 Hendrik Schröter, Tobias Rosenkranz, Alberto N. Escalante-B., Andreas Maier

Multi-frame algorithms for single-channel speech enhancement are able to take advantage from short-time correlations within the speech signal.

Speech Enhancement

A Platform for the Biomedical Application of Large Language Models

3 code implementations10 May 2023 Sebastian Lobentanzer, Shaohong Feng, The BioChatter Consortium, Andreas Maier, Cankun Wang, Jan Baumbach, Nils Krehl, Qin Ma, Julio Saez-Rodriguez

Current-generation Large Language Models (LLMs) have stirred enormous interest in recent months, yielding great potential for accessibility and automation, while simultaneously posing significant challenges and risk of misuse.

Benchmarking Privacy Preserving +1

Scale-Equivariant Deep Learning for 3D Data

1 code implementation12 Apr 2023 Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang, Moritz Zaiss, Andreas Maier, Daniel Cremers

The ability of convolutional neural networks (CNNs) to recognize objects regardless of their position in the image is due to the translation-equivariance of the convolutional operation.

Image Segmentation Medical Image Segmentation +1

Unsupervised detection of small hyperreflective features in ultrahigh resolution optical coherence tomography

no code implementations26 Mar 2023 Marcel Reimann, Jungeun Won, Hiroyuki Takahashi, Antonio Yaghy, Yunchan Hwang, Stefan Ploner, Junhong Lin, Jessica Girgis, Kenneth Lam, Siyu Chen, Nadia K. Waheed, Andreas Maier, James G. Fujimoto

Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases.

BOSS: Bones, Organs and Skin Shape Model

no code implementations8 Mar 2023 Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan, Norbert Strobel, Bernhard Egger, Markus Kowarschik, Andreas Maier

Objective: A digital twin of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided interventions.

Exploring Epipolar Consistency Conditions for Rigid Motion Compensation in In-vivo X-ray Microscopy

no code implementations1 Mar 2023 Mareike Thies, Fabian Wagner, Mingxuan Gu, Siyuan Mei, Yixing Huang, Sabrina Pechmann, Oliver Aust, Daniela Weidner, Georgiana Neag, Stefan Uderhardt, Georg Schett, Silke Christiansen, Andreas Maier

Intravital X-ray microscopy (XRM) in preclinical mouse models is of vital importance for the identification of microscopic structural pathological changes in the bone which are characteristic of osteoporosis.

Motion Compensation

Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals

1 code implementation1 Mar 2023 Susu Sun, Stefano Woerner, Andreas Maier, Lisa M. Koch, Christian F. Baumgartner

Furthermore, as we show in this paper, current explanation techniques do not perform adequately in the multi-label scenario, in which multiple medical findings may co-occur in a single image.

Classification Clinical Knowledge +1

Risk Classification of Brain Metastases via Radiomics, Delta-Radiomics and Machine Learning

no code implementations17 Feb 2023 Philipp Sommer, Yixing Huang, Christoph Bert, Andreas Maier, Manuel Schmidt, Arnd Dörfler, Rainer Fietkau, Florian Putz

We hypothesized that using radiomics and machine learning (ML), metastases at high risk for subsequent progression could be identified during follow-up prior to the onset of significant tumor growth, enabling personalized follow-up intervals and early selection for salvage treatment.

Word class representations spontaneously emerge in a deep neural network trained on next word prediction

no code implementations15 Feb 2023 Kishore Surendra, Achim Schilling, Paul Stoewer, Andreas Maier, Patrick Krauss

Strikingly, we find that the internal representations of nine-word input sequences cluster according to the word class of the tenth word to be predicted as output, even though the neural network did not receive any explicit information about syntactic rules or word classes during training.

Language Acquisition

Optimizing CT Scan Geometries With and Without Gradients

no code implementations13 Feb 2023 Mareike Thies, Fabian Wagner, Noah Maul, Laura Pfaff, Linda-Sophie Schneider, Christopher Syben, Andreas Maier

In computed tomography (CT), the projection geometry used for data acquisition needs to be known precisely to obtain a clear reconstructed image.

Computed Tomography (CT) Motion Compensation

Geometric Constraints Enable Self-Supervised Sinogram Inpainting in Sparse-View Tomography

no code implementations13 Feb 2023 Fabian Wagner, Mareike Thies, Noah Maul, Laura Pfaff, Oliver Aust, Sabrina Pechmann, Christopher Syben, Andreas Maier

By reconstructing independent stacks of projection data, a self-supervised loss is calculated in the CT image domain and used to directly optimize projection image intensities to match the missing tomographic views constrained by the projection geometry.

Computed Tomography (CT) SSIM

ODOR: The ICPR2022 ODeuropa Challenge on Olfactory Object Recognition

no code implementations24 Jan 2023 Mathias Zinnen, Prathmesh Madhu, Ronak Kosti, Peter Bell, Andreas Maier, Vincent Christlein

The Odeuropa Challenge on Olfactory Object Recognition aims to foster the development of object detection in the visual arts and to promote an olfactory perspective on digital heritage.

Domain Adaptation Few-Shot Learning +4

Transfer Learning for Olfactory Object Detection

no code implementations24 Jan 2023 Mathias Zinnen, Prathmesh Madhu, Peter Bell, Andreas Maier, Vincent Christlein

We investigate the effect of style and category similarity in multiple datasets used for object detection pretraining.

Object object-detection +2

Classification of Luminal Subtypes in Full Mammogram Images Using Transfer Learning

no code implementations23 Jan 2023 Adarsh Bhandary Panambur, Prathmesh Madhu, Andreas Maier

Automatic identification of patients with luminal and non-luminal subtypes during a routine mammography screening can support clinicians in streamlining breast cancer therapy planning.

Breast Cancer Detection Classification +1

Multi-Scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset

1 code implementation11 Jan 2023 Frauke Wilm, Marco Fragoso, Christof A. Bertram, Nikolas Stathonikos, Mathias Öttl, Jingna Qiu, Robert Klopfleisch, Andreas Maier, Katharina Breininger, Marc Aubreville

Additionally, to quantify the inherent scanner-induced domain shift, we train a tumor segmentation network on each scanner subset and evaluate the performance both in- and cross-domain.

Domain Generalization Tumor Segmentation

Metal-conscious Embedding for CBCT Projection Inpainting

no code implementations29 Nov 2022 Fuxin Fan, Yangkong Wang, Ludwig Ritschl, Ramyar Biniazan, Marcel Beister, Björn Kreher, Yixing Huang, Steffen Kappler, Andreas Maier

The existence of metallic implants in projection images for cone-beam computed tomography (CBCT) introduces undesired artifacts which degrade the quality of reconstructed images.

Metal Artifact Reduction

PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation

1 code implementation CVPR 2023 Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan, Norbert Strobel, Markus Kowarschik, Andreas Maier, Bernhard Egger

Current techniques directly regress the shape, pose, and translation of a parametric model from an input image through a non-linear mapping with minimal flexibility to any external influences.

Ranked #3 on 3D Human Pose Estimation on 3DPW (using extra training data)

3D Human Pose Estimation Camera Calibration +1

Improved HER2 Tumor Segmentation with Subtype Balancing using Deep Generative Networks

no code implementations11 Nov 2022 Mathias Öttl, Jana Mönius, Matthias Rübner, Carol I. Geppert, Jingna Qiu, Frauke Wilm, Arndt Hartmann, Matthias W. Beckmann, Peter A. Fasching, Andreas Maier, Ramona Erber, Katharina Breininger

We show the suitability of Generative Adversarial Networks (GANs) and especially diffusion models to create realistic images based on subtype-conditioning for the use case of HER2-stained histopathology.

Segmentation Tumor Segmentation

An unobtrusive quality supervision approach for medical image annotation

no code implementations11 Nov 2022 Sonja Kunzmann, Mathias Öttl, Prathmesh Madhu, Felix Denzinger, Andreas Maier

Users could not detect 52. 12% of generated images by DM proofing the feasibility to replace the original cells with synthetic cells without being noticed.

whole slide images

Employing Graph Representations for Cell-level Characterization of Melanoma MELC Samples

no code implementations10 Nov 2022 Luis Carlos Rivera Monroy, Leonhard Rist, Martin Eberhardt, Christian Ostalecki, Andreas Baur, Julio Vera, Katharina Breininger, Andreas Maier

For this reason, computer-assisted approaches have gained popularity and shown promising results in tasks such as segmentation and classification of skin disorders.


Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems

no code implementations2 Nov 2022 Kai Packhäuser, Lukas Folle, Florian Thamm, Andreas Maier

The availability of large-scale chest X-ray datasets is a requirement for developing well-performing deep learning-based algorithms in thoracic abnormality detection and classification.

Anomaly Detection Image Generation +1

On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting

1 code implementation2 Nov 2022 Fabian Wagner, Mareike Thies, Laura Pfaff, Oliver Aust, Sabrina Pechmann, Daniela Weidner, Noah Maul, Maximilian Rohleder, Mingxuan Gu, Jonas Utz, Felix Denzinger, Andreas Maier

In this work, we present an end-to-end trainable CT reconstruction pipeline that contains denoising operators in both the projection and the image domain and that are optimized simultaneously without requiring ground-truth high-dose CT data.

Computed Tomography (CT) Image Denoising +1

Neural Network based Formation of Cognitive Maps of Semantic Spaces and the Emergence of Abstract Concepts

no code implementations28 Oct 2022 Paul Stoewer, Achim Schilling, Andreas Maier, Patrick Krauss

The neural network successfully learns the similarities between different animal species, and constructs a cognitive map of 'animal space' based on the principle of successor representations with an accuracy of around 30% which is near to the theoretical maximum regarding the fact that all animal species have more than one possible successor, i. e. nearest neighbor in feature space.

ArtFacePoints: High-resolution Facial Landmark Detection in Paintings and Prints

1 code implementation17 Oct 2022 Aline Sindel, Andreas Maier, Vincent Christlein

Facial landmark detection plays an important role for the similarity analysis in artworks to compare portraits of the same or similar artists.

Facial Landmark Detection Image Registration +2

Self-Supervised 2D/3D Registration for X-Ray to CT Image Fusion

no code implementations14 Oct 2022 Srikrishna Jaganathan, Maximilian Kukla, Jian Wang, Karthik Shetty, Andreas Maier

Deep Learning-based 2D/3D registration enables fast, robust, and accurate X-ray to CT image fusion when large annotated paired datasets are available for training.

Domain Adaptation

Metal Inpainting in CBCT Projections Using Score-based Generative Model

no code implementations20 Sep 2022 Siyuan Mei, Fuxin Fan, Andreas Maier

During orthopaedic surgery, the inserting of metallic implants or screws are often performed under mobile C-arm systems.

Metal Artifact Reduction

A Spatiotemporal Model for Precise and Efficient Fully-automatic 3D Motion Correction in OCT

no code implementations15 Sep 2022 Stefan Ploner, Siyu Chen, Jungeun Won, Lennart Husvogt, Katharina Breininger, Julia Schottenhamml, James Fujimoto, Andreas Maier

Optical coherence tomography (OCT) is a micrometer-scale, volumetric imaging modality that has become a clinical standard in ophthalmology.


A Multi-modal Registration and Visualization Software Tool for Artworks using CraquelureNet

no code implementations18 Aug 2022 Aline Sindel, Andreas Maier, Vincent Christlein

For art investigations of paintings, multiple imaging technologies, such as visual light photography, infrared reflectography, ultraviolet fluorescence photography, and x-radiography are often used.

Multi-modal Retinal Image Registration Using a Keypoint-Based Vessel Structure Aligning Network

no code implementations21 Jul 2022 Aline Sindel, Bettina Hohberger, Andreas Maier, Vincent Christlein

Our method extracts convolutional features from the vessel structure for keypoint detection and description and uses a graph neural network for feature matching.

Image Registration Keypoint Detection

Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT

no code implementations15 Jul 2022 Fabian Wagner, Mareike Thies, Felix Denzinger, Mingxuan Gu, Mayank Patwari, Stefan Ploner, Noah Maul, Laura Pfaff, Yixing Huang, Andreas Maier

Low-dose computed tomography (CT) denoising algorithms aim to enable reduced patient dose in routine CT acquisitions while maintaining high image quality.

Computed Tomography (CT) Denoising

AutoSpeed: A Linked Autoencoder Approach for Pulse-Echo Speed-of-Sound Imaging for Medical Ultrasound

no code implementations4 Jul 2022 Farnaz Khun Jush, Markus Biele, Peter M. Dueppenbecker, Andreas Maier

On the measured data, the predictions of the proposed method are close to the expected values with MAPE of 1. 1%.

ICC++: Explainable Image Retrieval for Art Historical Corpora using Image Composition Canvas

no code implementations22 Jun 2022 Prathmesh Madhu, Tilman Marquart, Ronak Kosti, Dirk Suckow, Peter Bell, Andreas Maier, Vincent Christlein

In this work, we present a novel approach called Image Composition Canvas (ICC++) to compare and retrieve images having similar compositional elements.

Image Retrieval Retrieval

ConFUDA: Contrastive Fewshot Unsupervised Domain Adaptation for Medical Image Segmentation

no code implementations8 Jun 2022 Mingxuan Gu, Sulaiman Vesal, Mareike Thies, Zhaoya Pan, Fabian Wagner, Mirabela Rusu, Andreas Maier, Ronak Kosti

Then, to align the source and target features and tackle the memory issue of the traditional contrastive loss, we propose the centroid-based contrastive learning (CCL) and a centroid norm regularizer (CNR) to optimize the contrastive pairs in both direction and magnitude.

Contrastive Learning Image Segmentation +4

DeepTechnome: Mitigating Unknown Bias in Deep Learning Based Assessment of CT Images

no code implementations26 May 2022 Simon Langer, Oliver Taubmann, Felix Denzinger, Andreas Maier, Alexander Mühlberg

Reliably detecting diseases using relevant biological information is crucial for real-world applicability of deep learning techniques in medical imaging.

Building Brains: Subvolume Recombination for Data Augmentation in Large Vessel Occlusion Detection

no code implementations5 May 2022 Florian Thamm, Oliver Taubmann, Markus Jürgens, Aleksandra Thamm, Felix Denzinger, Leonhard Rist, Hendrik Ditt, Andreas Maier

The best configuration detects LVOs with an AUC of 0. 91, LVOs in the ICA with an AUC of 0. 96, and in the MCA with 0. 91 while accurately predicting the affected side.

Data Augmentation

An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes

no code implementations26 Apr 2022 Florian Thamm, Markus Jürgens, Oliver Taubmann, Aleksandra Thamm, Leonhard Rist, Hendrik Ditt, Andreas Maier

In the work at hand, we place the algorithm in a clinical context by evaluating the labeling and occlusion detection on stroke patients, where we have achieved labeling sensitivities comparable to other works between 92\,\% and 95\,\%.


Continual Learning for Peer-to-Peer Federated Learning: A Study on Automated Brain Metastasis Identification

no code implementations26 Apr 2022 Yixing Huang, Christoph Bert, Stefan Fischer, Manuel Schmidt, Arnd Dörfler, Andreas Maier, Rainer Fietkau, Florian Putz

With iterative continual learning (i. e., the shared model revisits each center multiple times during training), the sensitivity is further improved to 0. 914, which is identical to the sensitivity using mixed data for training.

Continual Learning Federated Learning

The effect of speech pathology on automatic speaker verification -- a large-scale study

1 code implementation13 Apr 2022 Soroosh Tayebi Arasteh, Tobias Weise, Maria Schuster, Elmar Noeth, Andreas Maier, Seung Hee Yang

Navigating the challenges of data-driven speech processing, one of the primary hurdles is accessing reliable pathological speech data.

Text-Independent Speaker Verification

Disentangled Latent Speech Representation for Automatic Pathological Intelligibility Assessment

1 code implementation8 Apr 2022 Tobias Weise, Philipp Klumpp, Kubilay Can Demir, Andreas Maier, Elmar Noeth, Bjoern Heismann, Maria Schuster, Seung Hee Yang

Our results are among the first to show that disentangled speech representations can be used for automatic pathological speech intelligibility assessment, resulting in a reference speaker pair invariant method, applicable in scenarios with only few utterances available.

Simulation-Driven Training of Vision Transformers Enabling Metal Segmentation in X-Ray Images

no code implementations17 Mar 2022 Fuxin Fan, Ludwig Ritschl, Marcel Beister, Ramyar Biniazan, Björn Kreher, Tristan M. Gottschalk, Steffen Kappler, Andreas Maier

Since the generation of high quality clinical training is a constant challenge, this study proposes to generate simulated X-ray images based on CT data sets combined with self-designed computer aided design (CAD) implants and make use of convolutional neural network (CNN) and vision transformer (ViT) for metal segmentation.

Segmentation Test

Neural Network based Successor Representations of Space and Language

no code implementations22 Feb 2022 Paul Stoewer, Christian Schlieker, Achim Schilling, Claus Metzner, Andreas Maier, Patrick Krauss

We conclude that cognitive maps and neural network-based successor representations of structured knowledge provide a promising way to overcome some of the short comings of deep learning towards artificial general intelligence.

Deep learning-guided weighted averaging for signal dropout compensation in diffusion-weighted imaging of the liver

no code implementations20 Feb 2022 Fasil Gadjimuradov, Thomas Benkert, Marcel Dominik Nickel, Tobit Führes, Marc Saake, Andreas Maier

Methods: Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed which aims to suppress the contribution of image regions affected by signal dropouts.

Learning Perspective Deformation in X-Ray Transmission Imaging

no code implementations13 Feb 2022 Yixing Huang, Andreas Maier, Fuxin Fan, Björn Kreher, Xiaolin Huang, Rainer Fietkau, Christoph Bert, Florian Putz

The complementary view setting provides a practical way to identify perspectively deformed structures by assessing the deviation between the two views.

CAD-RADS Scoring using Deep Learning and Task-Specific Centerline Labeling

no code implementations8 Feb 2022 Felix Denzinger, Michael Wels, Oliver Taubmann, Mehmet A. Gülsün, Max Schöbinger, Florian André, Sebastian J. Buss, Johannes Görich, Michael Sühling, Andreas Maier, Katharina Breininger

With coronary artery disease (CAD) persisting to be one of the leading causes of death worldwide, interest in supporting physicians with algorithms to speed up and improve diagnosis is high.

SliTraNet: Automatic Detection of Slide Transitions in Lecture Videos using Convolutional Neural Networks

1 code implementation7 Feb 2022 Aline Sindel, Abner Hernandez, Seung Hee Yang, Vincent Christlein, Andreas Maier

With the increasing number of online learning material in the web, search for specific content in lecture videos can be time consuming.

Deep Learning for Ultrasound Speed-of-Sound Reconstruction: Impacts of Training Data Diversity on Stability and Robustness

no code implementations1 Feb 2022 Farnaz Khun Jush, Markus Biele, Peter M. Dueppenbecker, Andreas Maier

Ultrasound b-mode imaging is a qualitative approach and diagnostic quality strongly depends on operators' training and experience.

Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset

1 code implementation27 Jan 2022 Frauke Wilm, Marco Fragoso, Christian Marzahl, Jingna Qiu, Chloé Puget, Laura Diehl, Christof A. Bertram, Robert Klopfleisch, Andreas Maier, Katharina Breininger, Marc Aubreville

Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging.

whole slide images

Initial Investigations Towards Non-invasive Monitoring of Chronic Wound Healing Using Deep Learning and Ultrasound Imaging

no code implementations25 Jan 2022 Maja Schlereth, Daniel Stromer, Yash Mantri, Jason Tsujimoto, Katharina Breininger, Andreas Maier, Caesar Anderson, Pranav S. Garimella, Jesse V. Jokerst

We conclude that deep learning-supported analysis of non-invasive ultrasound images is a promising area of research to automatically extract cross-sectional wound size and depth information with potential value in monitoring response to therapy.

Ultra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography

1 code implementation25 Jan 2022 Fabian Wagner, Mareike Thies, Mingxuan Gu, Yixing Huang, Sabrina Pechmann, Mayank Patwari, Stefan Ploner, Oliver Aust, Stefan Uderhardt, Georg Schett, Silke Christiansen, Andreas Maier

Due to the extremely low number of trainable parameters with well-defined effect, prediction reliance and data integrity is guaranteed at any time in the proposed pipelines, in contrast to most other deep learning-based denoising architectures.

Denoising SSIM

Superpixel Pre-Segmentation of HER2 Slides for Efficient Annotation

no code implementations19 Jan 2022 Mathias Öttl, Jana Mönius, Christian Marzahl, Matthias Rübner, Carol I. Geppert, Arndt Hartmann, Matthias W. Beckmann, Peter Fasching, Andreas Maier, Ramona Erber, Katharina Breininger

When evaluating the approaches on fully manually annotated images, we observe that the autoencoder-based superpixels achieve a 23% increase in boundary F1 score compared to the baseline SLIC superpixels.

Clustering Denoising +5

Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential Equations

no code implementations19 Jan 2022 Mareike Thies, Fabian Wagner, Mingxuan Gu, Lukas Folle, Lina Felsner, Andreas Maier

Learned iterative reconstruction algorithms for inverse problems offer the flexibility to combine analytical knowledge about the problem with modules learned from data.

Numerical Integration

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data

1 code implementation22 Dec 2021 Yixing Huang, Christoph Bert, Philipp Sommer, Benjamin Frey, Udo Gaipl, Luitpold V. Distel, Thomas Weissmann, Michael Uder, Manuel A. Schmidt, Arnd Dörfler, Andreas Maier, Rainer Fietkau, Florian Putz

To improve brain metastasis detection performance with deep learning, a custom detection loss called volume-level sensitivity-specificity (VSS) is proposed, which rates individual metastasis detection sensitivity and specificity in (sub-)volume levels.

Ensemble Learning Specificity

Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning

2 code implementations6 Dec 2021 Lukas Bommes, Mathis Hoffmann, Claudia Buerhop-Lutz, Tobias Pickel, Jens Hauch, Christoph Brabec, Andreas Maier, Ian Marius Peters

Instead, we frame fault detection as more realistic unsupervised domain adaptation problem where we train on labelled data of one source PV plant and make predictions on another target plant.

Anomaly Detection Contrastive Learning +2

Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? -- A Case Study using Dual Energy CT Data

no code implementations6 Dec 2021 Andreas Maier, Seung Hee Yang, Farhad Maleki, Nikesh Muthukrishnan, Reza Forghani

In the domain of medical image processing, medical device manufacturers protect their intellectual property in many cases by shipping only compiled software, i. e. binary code which can be executed but is difficult to be understood by a potential attacker.

Towards Super-Resolution CEST MRI for Visualization of Small Structures

1 code implementation3 Dec 2021 Lukas Folle, Katharian Tkotz, Fasil Gadjimuradov, Lorenz Kapsner, Moritz Fabian, Sebastian Bickelhaupt, David Simon, Arnd Kleyer, Gerhard Krönke, Moritz Zaiß, Armin Nagel, Andreas Maier

This work paves the way for the prospective investigation of neural networks for super-resolution CEST MRI and, followingly, might lead to a earlier detection of the onset of rheumatic diseases.

Anatomy SSIM +1

Detection of Large Vessel Occlusions using Deep Learning by Deforming Vessel Tree Segmentations

no code implementations3 Dec 2021 Florian Thamm, Oliver Taubmann, Markus Jürgens, Hendrik Ditt, Andreas Maier

Training the EfficientNetB1 architecture on 100 data sets, the proposed augmentation scheme was able to raise the ROC AUC to 0. 85 from a baseline value of 0. 56 using no augmentation.

Prediction of Household-level Heat-Consumption using PSO enhanced SVR Model

no code implementations3 Dec 2021 Satyaki Chatterjee, Siming Bayer, Andreas Maier

In combating climate change, an effective demand-based energy supply operation of the district energy system (DES) for heating or cooling is indispensable.

Automatic Plane Adjustment of Orthopedic Intra-operative Flat Panel Detector CT-Volumes

no code implementations15 Sep 2021 Celia Martin Vicario, Florian Kordon, Felix Denzinger, Jan Siad El Barbari, Maxim Privalov, Jochen Franke, Sarina Thomas, Lisa Kausch, Andreas Maier, Holger Kunze

The most important benefit of the MTL approach is that it is a single network for standard plane regression for all body regions with a reduced number of stored parameters.

Multi-Task Learning regression

Automated Cardiac Resting Phase Detection Targeted on the Right Coronary Artery

no code implementations6 Sep 2021 Seung Su Yoon, Elisabeth Preuhs, Michaela Schmidt, Christoph Forman, Teodora Chitiboi, Puneet Sharma, Juliano Lara Fernandes, Christoph Tillmanns, Jens Wetzl, Andreas Maier

In this work, automated RP detection has been introduced by the proposed framework and demonstrated feasibility, robustness, and applicability for static imaging acquisitions.


Module-Power Prediction from PL Measurements using Deep Learning

no code implementations31 Aug 2021 Mathis Hoffmann, Johannes Hepp, Bernd Doll, Claudia Buerhop-Lutz, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein

While these areas can be easily identified from electroluminescense (EL) images, this is much harder for photoluminescence (PL) images.


InSE-NET: A Perceptually Coded Audio Quality Model based on CNN

no code implementations30 Aug 2021 Guanxin Jiang, Arijit Biswas, Christian Bergler, Andreas Maier

Automatic coded audio quality assessment is an important task whose progress is hampered by the scarcity of human annotations, poor generalization to unseen codecs, bitrates, content-types, and a lack of flexibility of existing approaches.

Data Augmentation

Fiducial marker recovery and detection from severely truncated data in navigation assisted spine surgery

no code implementations25 Aug 2021 Fuxin Fan, Björn Kreher, Holger Keil, Andreas Maier, Yixing Huang

For direct detection from distorted markers in reconstructed volumes, an efficient automatic marker detection method using two neural networks and a conventional circle detection algorithm is proposed.

Deep Iterative 2D/3D Registration

no code implementations21 Jul 2021 Srikrishna Jaganathan, Jian Wang, Anja Borsdorf, Karthik Shetty, Andreas Maier

A refinement step using the classical optimization-based 2D/3D registration method applied in combination with Deep Learning-based techniques can provide the required accuracy.

Optical Flow Estimation

SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators

1 code implementation21 May 2021 Alexander Mattick, Martin Mayr, Mathias Seuret, Andreas Maier, Vincent Christlein

As of recent generative adversarial networks have allowed for big leaps in the realism of generated images in diverse domains, not the least of which being handwritten text generation.

Data Augmentation Handwritten Text Recognition +1

Robust partial Fourier reconstruction for diffusion-weighted imaging using a recurrent convolutional neural network

no code implementations19 May 2021 Fasil Gadjimuradov, Thomas Benkert, Marcel Dominik Nickel, Andreas Maier

The algorithm is trained on DW liver data of 60 volunteers and evaluated on retrospectively and prospectively sub-sampled data of different anatomies and resolutions.

Rolling Shutter Correction

MR-Contrast-Aware Image-to-Image Translations with Generative Adversarial Networks

no code implementations3 Apr 2021 Jonas Denck, Jens Guehring, Andreas Maier, Eva Rothgang

Our approach is motivated by style transfer networks, whereas the "style" for an image is explicitly given in our case, as it is determined by the MR acquisition parameters our network is conditioned on.

Data Augmentation Generative Adversarial Network +1

Quantifying the Scanner-Induced Domain Gap in Mitosis Detection

1 code implementation30 Mar 2021 Marc Aubreville, Christof Bertram, Mitko Veta, Robert Klopfleisch, Nikolas Stathonikos, Katharina Breininger, Natalie ter Hoeve, Francesco Ciompi, Andreas Maier

Hypothesizing that the scanner device plays a decisive role in this effect, we evaluated the susceptibility of a standard mitosis detection approach to the domain shift introduced by using a different whole slide scanner.

Mitosis Detection

Deep Learning-based Patient Re-identification Is able to Exploit the Biometric Nature of Medical Chest X-ray Data

1 code implementation15 Mar 2021 Kai Packhäuser, Sebastian Gündel, Nicolas Münster, Christopher Syben, Vincent Christlein, Andreas Maier

Our verification system is able to identify whether two frontal chest X-ray images are from the same person with an AUC of 0. 9940 and a classification accuracy of 95. 55%.


Pixel-wise Distance Regression for Glacier Calving Front Detection and Segmentation

no code implementations9 Mar 2021 Amirabbas Davari, Christoph Baller, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein

In this work, we propose to mitigate the class-imbalance between the calving front class and the non-calving front class by reformulating the segmentation problem into a pixel-wise regression task.

Distance regression regression

Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks

no code implementations17 Feb 2021 Jonas Denck, Jens Guehring, Andreas Maier, Eva Rothgang

A Magnetic Resonance Imaging (MRI) exam typically consists of the acquisition of multiple MR pulse sequences, which are required for a reliable diagnosis.

Generative Adversarial Network Image Generation

Learning the Update Operator for 2D/3D Image Registration

no code implementations4 Feb 2021 Srikrishna Jaganathan, Jian Wang, Anja Borsdorf, Andreas Maier

We aim to address this gap by incorporating traditional methods in deep neural networks using known operator learning.

Computational Efficiency Image Registration +1

Learning-Based Patch-Wise Metal Segmentation with Consistency Check

no code implementations26 Jan 2021 Tristan M. Gottschalk, Andreas Maier, Florian Kordon, Björn W. Kreher

Metal implants that are inserted into the patient's body during trauma interventions cause heavy artifacts in 3D X-ray acquisitions.

Metal Artifact Reduction Segmentation

X-ray Scatter Estimation Using Deep Splines

no code implementations22 Jan 2021 Philipp Roser, Annette Birkhold, Alexander Preuhs, Christopher Syben, Lina Felsner, Elisabeth Hoppe, Norbert Strobel, Markus Korwarschik, Rebecca Fahrig, Andreas Maier

Algorithmic X-ray scatter compensation is a desirable technique in flat-panel X-ray imaging and cone-beam computed tomography.

Medical Physics Image and Video Processing

Learning to be EXACT, Cell Detection for Asthma on Partially Annotated Whole Slide Images

no code implementations13 Jan 2021 Christian Marzahl, Christof A. Bertram, Frauke Wilm, Jörn Voigt, Ann K. Barton, Robert Klopfleisch, Katharina Breininger, Andreas Maier, Marc Aubreville

We evaluated our pipeline in a cross-validation setup with a fixed training set using a dataset of six equine WSIs of which four are partially annotated and used for training, and two fully annotated WSI are used for validation and testing.

Cell Detection object-detection +2

Coronary Plaque Analysis for CT Angiography Clinical Research

no code implementations11 Jan 2021 Felix Denzinger, Michael Wels, Christian Hopfgartner, Jing Lu, Max Schöbinger, Andreas Maier, Michael Sühling

However, to enable clinical research with the help of these algorithms, a software solution, which enables manual correction, comprehensive visual feedback and tissue analysis capabilities, is needed.


Glacier Calving Front Segmentation Using Attention U-Net

no code implementations8 Jan 2021 Michael Holzmann, Amirabbas Davari, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein

An essential climate variable to determine the tidewater glacier status is the location of the calving front position and the separation of seasonal variability from long-term trends.

2-D Respiration Navigation Framework for 3-D Continuous Cardiac Magnetic Resonance Imaging

no code implementations26 Dec 2020 Elisabeth Hoppe, Jens Wetzl, Philipp Roser, Lina Felsner, Alexander Preuhs, Andreas Maier

Continuous protocols for cardiac magnetic resonance imaging enable sampling of the cardiac anatomy simultaneously resolved into cardiac phases.


Spatio-temporal Multi-task Learning for Cardiac MRI Left Ventricle Quantification

1 code implementation24 Dec 2020 Sulaiman Vesal, Mingxuan Gu, Andreas Maier, Nishant Ravikumar

In this paper, we propose a spatio-temporal multi-task learning approach to obtain a complete set of measurements quantifying cardiac LV morphology, regional-wall thickness (RWT), and additionally detecting the cardiac phase cycle (systole and diastole) for a given 3D Cine-magnetic resonance (MR) image sequence.

Model Optimization Multi-Task Learning

Combined subleading high-energy logarithms and NLO accuracy for W production in association with multiple jets

no code implementations18 Dec 2020 Jeppe R. Andersen, James A. Black, Helen M. Brooks, Emmet P. Byrne, Andreas Maier, Jennifer M. Smillie

Large logarithmic corrections in $\hat s/p_t^2$ lead to substantial variations in the perturbative predictions for inclusive $W$-plus-dijet processes at the Large Hadron Collider.

High Energy Physics - Phenomenology

Enhancing Human Pose Estimation in Ancient Vase Paintings via Perceptually-grounded Style Transfer Learning

1 code implementation10 Dec 2020 Prathmesh Madhu, Angel Villar-Corrales, Ronak Kosti, Torsten Bendschus, Corinna Reinhardt, Peter Bell, Andreas Maier, Vincent Christlein

(2) To improve the already strong results further, we created a small dataset (ClassArch) consisting of ancient Greek vase paintings from the 6-5th century BCE with person and pose annotations.

Image Retrieval Pose Estimation +3

Robustness Investigation on Deep Learning CT Reconstruction for Real-Time Dose Optimization

no code implementations7 Dec 2020 Chang Liu, Yixing Huang, Joscha Maier, Laura Klein, Marc Kachelrieß, Andreas Maier

For organ-specific AEC, a preliminary CT reconstruction is necessary to estimate organ shapes for dose optimization, where only a few projections are allowed for real-time reconstruction.

Computed Tomography (CT) Image Reconstruction +1

ICFHR 2020 Competition on Image Retrieval for Historical Handwritten Fragments

1 code implementation20 Oct 2020 Mathias Seuret, Anguelos Nicolaou, Dominique Stutzmann, Andreas Maier, Vincent Christlein

In particular, we investigate the performance of large-scale retrieval of historical document fragments in terms of style and writer identification.

Image Retrieval Retrieval

Automatic CAD-RADS Scoring Using Deep Learning

no code implementations5 Oct 2020 Felix Denzinger, Michael Wels, Katharina Breininger, Mehmet A. Gülsün, Max Schöbinger, Florian André, Sebastian Buß, Johannes Görich, Michael Sühling, Andreas Maier

Coronary CT angiography (CCTA) has established its role as a non-invasive modality for the diagnosis of coronary artery disease (CAD).