Search Results for author: Carsten Marr

Found 14 papers, 8 papers with code

BEL: A Bag Embedding Loss for Transformer enhances Multiple Instance Whole Slide Image Classification

no code implementations2 Mar 2023 Daniel Sens, Ario Sadafi, Francesco Paolo Casale, Nassir Navab, Carsten Marr

Recent MIL approaches produce highly informative bag level representations by utilizing the transformer architecture's ability to model the dependencies between instances.

Image Classification Multiple Instance Learning +1

A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images

1 code implementation30 Aug 2022 Dominik J. E. Waibel, Ernst Röell, Bastian Rieck, Raja Giryes, Carsten Marr

Diffusion models are a special type of generative model, capable of synthesising new data from a learnt distribution.

Data Augmentation

Anomaly-aware multiple instance learning for rare anemia disorder classification

1 code implementation4 Jul 2022 Salome Kazeminia, Ario Sadafi, Asya Makhro, Anna Bogdanova, Shadi Albarqouni, Carsten Marr

Deep learning-based classification of rare anemia disorders is challenged by the lack of training data and instance-level annotations.

Classification Multiple Instance Learning

Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification

1 code implementation1 Jul 2022 Raheleh Salehi, Ario Sadafi, Armin Gruber, Peter Lienemann, Nassir Navab, Shadi Albarqouni, Carsten Marr

Here, we propose a cross-domain adapted autoencoder to extract features in an unsupervised manner on three different datasets of single white blood cells scanned from peripheral blood smears.

Image Classification

DeStripe: A Self2Self Spatio-Spectral Graph Neural Network with Unfolded Hessian for Stripe Artifact Removal in Light-sheet Microscopy

no code implementations27 Jun 2022 Yu Liu, Kurt Weiss, Nassir Navab, Carsten Marr, Jan Huisken, Tingying Peng

Light-sheet fluorescence microscopy (LSFM) is a cutting-edge volumetric imaging technique that allows for three-dimensional imaging of mesoscopic samples with decoupled illumination and detection paths.


Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction

1 code implementation3 Mar 2022 Dominik J. E. Waibel, Scott Atwell, Matthias Meier, Carsten Marr, Bastian Rieck

We propose to complement geometrical shape information by including multi-scale topological features, such as connected components, cycles, and voids, in the reconstruction loss.

3D Reconstruction

InstantDL-An easy-to-use deep learning pipeline for image segmentation and classification

1 code implementation BMC Bioinformatics 2021 Dominik J. E. Waibel, Sayedali Shetab Boushehri, Carsten Marr

InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort.

Image Segmentation Instance Segmentation +1

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