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Breast Tumor Characterization Using [18F]FDG-PET/CT Imaging Combined with Data Preprocessing and Radiomics

Cancers 13, 1249

Journal Article

D. Krajnc, L. Papp, T. S. Nakuz, H. F. Magometschnigg, M. Grahovac, C. P. Spielvogel, B. Ecsedi, Z. Bago-Horvath, A. Haug, G. Karanikas, T. Beyer, M. Hacker, T. H. Helbich, K. Pinker

Supervised machine learning enables non-invasive lesion characterization in primary prostate cancer with [68Ga]Ga-PSMA-11 PET/MRI

European Journal of Nuclear Medicine and Molecular Imaging 48, 1795-1805

Journal Article

L. Papp, C. P. Spielvogel, B. Grubmuller, M. Grahovac, D. Krajnc, B. Ecsedi, R. A.M. Sareshgi, D. Mohamad, M. Hamboeck, I. Rausch, M. Mitterhauser, W. Wadsak, A. R. Haug, L. Kenner, P. Mazal, M. Susani, S. Hartenbach, P. Baltzer, T. H. Helbich, G. Kramer, S.F. Shariat, T. Beyer, M. Hartenbach, M. Hacker

Multi-lesion radiomics of PET/CT for non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma

European Radiology 32, 7056-7067

Journal Article

M. Zhao, K. Kluge, L. Papp, M. Grahovac, S. Yang, C. Jiang, D. Krajnc, C. Spielvogel, B. Ecsedi, A. Haug, S. Wang, M. Hacker, W. Zhang, X. Li

Automated data preparation for in vivo tumor characterization with machine learning

Frontiers in Oncology 12, 1017911

Journal Article

D. Krajnc, C. P. Spielvogel, M. Grahovac, B. Ecsedi, S. Rasul, N. Poetsch, T. Traub-Weidinger, A. R. Haug, Z. Ritter, H. Alizadeh, M. Hacker, T. Beyer, L. Papp

DEBI-NN: Distance-encoding biomorphic-informational neural networks for minimizing the number of trainable parameters

Neural Networks 167, 517-532

Journal Article

Laszlo Papp, David Haberl, Boglarka Ecsedi, Clemens P. Spielvogel, Denis Krajnc, Marko Grahovac, Sasan Moradi, Wolfgang Drexler
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Sex-specific radiomic features of L-[S-methyl-11C] methionine PET in patients with newly-diagnosed gliomas in relation to IDH1 predictability

Frontiers in Oncology 13, 986788

Journal Article

L. Papp, S. Rasul, C. P. Spielvogel, D. Krajnc, N. Poetsch, A. Woehrer, E-M. Patronas, B. Ecsedi, J. Furtner, M. Mitterhauser, I. Rausch, G. Widhalm, T. Beyer, M. Hacker, T. Traub-Weidinger

Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts

European Journal of Nuclear Medicine and Molecular Imaging

Journal Article

M. Grahovac, C. P. Spielvogel, D. Krajnc, B. Ecsedi, T. Traub-Weidinger, S. Rasul, K. Kluge, M. Zhao, X. Li, M. Hacker, A. Haug, L. Papp

DEBI-NN: Distance-Encoding Biomorphic-Informational Neural Networks in Medical Applications

AI+Science Summer School, University of Chicago Data Science Institute & IMSI - Poster

Poster

B. Ecsedi

DEBI-NN: Distance-Encoding Biomorphic-Informational Neural Networks in PET Radiomics

36th Annual Congress of the European Association of Nuclear Medicine (EANM), Vienna, Austria - Oral

Oral

B. Ecsedi, D. Haberl, C. P. Spielvogel, T. Traub-Weidinger, M. Hacker, L. Papp

AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images

The Twelfth International Conference on Learning Representations (ICLR 2024) - Poster

Poster

Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi, Viraj Prabhu, Judy Hoffman
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Incremental Role of Radiomics and Artificial Intelligence

Advanced Imaging and Therapy in Neuro-Oncology 161-172, Springer Nature Switzerland

Book chapter

L. Papp, C. Spielvogel, D. Haberl, B. Ecsedi

DEBI-NN Architecture Evaluation: Implications of Dataset Imbalance and Spatial Dropout on Performance

37th Annual Congress of the European Association of Nuclear Medicine (EANM) - Oral

Oral

A. Boukhari, B. Ecsedi, D. Haberl, C. Spielvogel, M. Hatt, L. Papp

In the search of optimal hyperparameter and network configurations of the novel DEBI-NN neural network for increased generalizability in small medical datasets

37th Annual Congress of the European Association of Nuclear Medicine (EANM) - Oral

Oral

B. Ecsedi, A. Boukhari, D. Haberl, C. Spielvogel, Zs. Ritter, H. Alizadeh, M. Hatt, L. Papp

Imaging Tumor Metabolism and Its Heterogeneity: Special Focus on Radiomics and AI

Interdisciplinary Cancer Research 1-26, Springer

Book chapter

L. Papp, D. Haberl, B. Ecsedi, M. Hatt, E. Lopci

Clinician-driven automated data preprocessing in nuclear medicine AI environments

European Journal of Nuclear Medicine and Molecular Imaging

Journal Article

D. Krajnc, C. Spielvogel, B. Ecsedi, Zs. Ritter, H. Alizadeh, M. Hacker, L. Papp

Model merging with SVD to Tie the KnOTS

The Thirteenth International Conference on Learning Representations (ICLR 2025) - Poster

Poster

George Stoica, Pratik Ramesh, Boglarka Ecsedi, Leshem Choshen, Judy Hoffman
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Scaling Laws in Model Merging: Investigating the Scaling Behavior of Merging LoRA Models

Georgia Institute of Technology, BSc Thesis (PURA Award)

BSc Thesis

Boglarka Ecsedi
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Impact of Regularization in Optimizing Distance-Encoding Biomorphic-Informational Neural Networks for Small Nuclear Medicine Datasets

EANM Innovation, 100008

Journal article

B. Ecsedi, A. Boukhari, C.P. Spielvogel, D. Haberl, Zs. Ritter, R.A. Bundschuh, C. Lapa, M. Hacker, M. Hatt, L. Papp

Genetic Algorithm vs. Gradient Descent for Training a Neural Network Architecture Dedicated to Low Data Regimes in Small Medical Datasets

Journal Article (in review)

Journal Article (in review)

A. Boukhari, B. Ecsedi, L. Papp, M. Hatt

Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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