Photo: Helmholtz Munich

Clinical & Academic Collaborators

Carsten Marr

Director, Institute of AI for Health, Helmholtz Munich; Professor of AI in Hematology and Cell Therapy, LMU University Hospital

Helmholtz Munich · LMU University Hospital Munich

Carsten Marr is founding director of the Institute of AI for Health at Helmholtz Munich and, since July 2025, Professor of AI in Hematology and Cell Therapy at LMU University Hospital. His lab develops AI for the diagnosis and treatment of blood disorders such as leukaemia. Awards include an ERC Consolidator Grant and the 2024 Eugen Münch Prize.

Research Collaboration and Funded Projects 1 filter all →

completed

Research collaboration · 2019 – 2022 · Rare Blood Disorders

Explainable AI for rare blood disorders

Collaboration with Carsten Marr (Helmholtz Munich) on explainable deep learning for diagnosing rare anaemias and blood cell disorders — attention-based and …

Medical Imaging Responsible AI Hematology

Publications 5 filter all →

Anomaly-aware multiple instance learning for rare anemia disorder classification

Salome Kazeminia, Ario Sadafi, Asya Makhro, Anna Bogdanova, Shadi Albarqouni, Carsten Marr

Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, Lecture Notes in Computer Science, 2022

Conference CORE A31% acc. Hematology Rare Blood Disorders

Publisher PDF Interactive explainer BibTeX

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

Raheleh Salehi, Ario Sadafi, Armin Gruber, Peter Lienemann, Nassir Navab, Shadi Albarqouni, Carsten Marr

Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, Lecture Notes in Computer Science, 2022

Conference CORE A31% acc. Hematology Rare Blood Disorders

Publisher PDF Interactive explainer BibTeX

Fourier Transform of Percoll Gradients Boosts CNN Classification of Hereditary Hemolytic Anemias

Ario Sadafi, Lucı́a Mar\á Moya Sans, Asya Makhro, Leonid Livshits, Nassir Navab, Anna Bogdanova, Shadi Albarqouni, Carsten Marr

2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021

Conference CORE B Hematology Rare Blood Disorders

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Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks

Ario Sadafi, Asya Makhro, Leonid Livshits, Nassir Navab, Anna Bogdanova, Shadi Albarqouni, Carsten Marr

Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021

Book / Chapter Hematology Rare Blood Disorders

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Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders

Ario Sadafi, Asya Makhro, Anna Bogdanova, Nassir Navab, Tingying Peng, Shadi Albarqouni, Carsten Marr

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020

Conference CORE A Hematology Rare Blood Disorders

Publisher PDF Interactive explainer BibTeX

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Research Collaboration and Funded Projects 1 filter all →

Explainable AI for rare blood disorders

Publications 5 filter all →

Anomaly-aware multiple instance learning for rare anemia disorder classification

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

Fourier Transform of Percoll Gradients Boosts CNN Classification of Hereditary Hemolytic Anemias

Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks

Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders