Deep Multiple Instance Hashing for Scalable Medical Image Retrieval. - Sailesh Conjeti; Magdalini Paschali; Amin Katouzian; Nassir Navab (MICCAI (3), 2017)

Learning Robust Hash Codes for Multiple Instance Image Retrieval. - Sailesh Conjeti; Magdalini Paschali; Amin Katouzian; Nassir Navab (CoRR, 2017)

Abstract: Deep Hashing for Large-Scale Medical Image Retrieval. - Sailesh Conjeti; Magdalini Paschali; Abhijit Guha Roy; Nassir Navab (Bildverarbeitung für die Medizin, 2018)

Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples. - Magdalini Paschali; Sailesh Conjeti; Fernando Navarro; Nassir Navab (MICCAI (1), 2018)

Generalizability vs. Robustness: Adversarial Examples for Medical Imaging. - Magdalini Paschali; Sailesh Conjeti; Fernando Navarro; Nassir Navab (CoRR, 2018)

Abstract: Adversarial Examples as Benchmark for Medical Imaging Neural Networks. - Magdalini Paschali; Sailesh Conjeti; Fernando Navarro; Nassir Navab (Bildverarbeitung für die Medizin, 2019)

Abstract: Beamforming Sub-Sampled Raw Ultrasound Data with DeepFormer. - Walter Simson; Magdalini Paschali; Guillaume Zahnd; Nassir Navab (Bildverarbeitung für die Medizin, 2019)

Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness. - Magdalini Paschali; Walter Simson; Abhijit Guha Roy; Rüdiger Göbl; Christian Wachinger; Nassir Navab (IPMI, 2019)

3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation. - Magdalini Paschali; Stefano Gasperini; Abhijit Guha Roy; Michael Y.-S. Fang; Nassir Navab (MICCAI (3), 2019)

Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness. - Magdalini Paschali; Walter Simson; Abhijit Guha Roy; Muhammad Ferjad Naeem; Rüdiger Göbl; Christian Wachinger; Nassir Navab (CoRR, 2019)

Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks. - Magdalini Paschali; Muhammad Ferjad Naeem; Walter Simson; Katja Steiger; Martin Mollenhauer; Nassir Navab (CoRR, 2019)

End-to-End Learning-Based Ultrasound Reconstruction. - Walter Simson; Rüdiger Göbl; Magdalini Paschali; Markus Krönke; Klemens Scheidhauer; Wolfgang Weber 005; Nassir Navab (CoRR, 2019)

Radar Emitter Classification with Attribute-specific Recurrent Neural Networks. - Paolo Notaro; Magdalini Paschali; Carsten Hopke; David Wittmann; Nassir Navab (CoRR, 2019)

Signal Clustering With Class-Independent Segmentation. - Stefano Gasperini; Magdalini Paschali; Carsten Hopke; David Wittmann; Nassir Navab (ICASSP, 2020)

Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning. - Hannes Hase; Mohammad Farid Azampour; Maria Tirindelli; Magdalini Paschali; Walter Simson; Emad Fatemizadeh; Nassir Navab (IROS, 2020)

TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks. - Tobias Czempiel; Magdalini Paschali; Matthias Keicher; Walter Simson; Hubertus Feussner; Seong Tae Kim 001; Nassir Navab (MICCAI (3), 2020)

Confidence-Based Out-of-Distribution Detection: A Comparative Study and Analysis. - Christoph Berger; Magdalini Paschali; Ben Glocker; Konstantinos Kamnitsas (UNSURE/PIPPI@MICCAI, 2021)

OperA: Attention-Regularized Transformers for Surgical Phase Recognition. - Tobias Czempiel; Magdalini Paschali; Daniel Ostler; Seong Tae Kim 001; Benjamin Busam; Nassir Navab (MICCAI (4), 2021)

Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. - Seong Tae Kim 001; Leili Goli; Magdalini Paschali; Ashkan Khakzar; Matthias Keicher; Tobias Czempiel; Egon Burian; Rickmer Braren; Nassir Navab; Thomas Wendler 001 (MICCAI (7), 2021)

Rethinking Ultrasound Augmentation: A Physics-Inspired Approach. - Maria Tirindelli; Christine Eilers; Walter Simson; Magdalini Paschali; Mohammad Farid Azampour; Nassir Navab (MICCAI (8), 2021)

U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome Prediction. - Matthias Keicher; Hendrik Burwinkel; David Bani-Harouni; Magdalini Paschali; Tobias Czempiel; Egon Burian; Marcus R. Makowski; Rickmer Braren; Nassir Navab; Thomas Wendler 001 (CoRR, 2021)

Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study. - Tobias Czempiel; Aidean Sharghi; Magdalini Paschali; Nassir Navab; Omid Mohareri (ECCV Workshops (3), 2022)

Bridging the Gap Between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing. - Magdalini Paschali; Qingyu Zhao; Ehsan Adeli 001; Kilian M. Pohl (PRIME@MICCAI, 2022)

Surgical Workflow Recognition: from Analysis of Challenges to Architectural Study. - Tobias Czempiel; Aidean Sharghi; Magdalini Paschali; Omid Mohareri (CoRR, 2022)

Longitudinal Self-Supervision for COVID-19 Pathology Quantification. - Tobias Czempiel; Coco Rogers; Matthias Keicher; Magdalini Paschali; Rickmer Braren; Egon Burian; Marcus R. Makowski; Nassir Navab; Thomas Wendler 001; Seong Tae Kim 001 (CoRR, 2022)

Self-supervised Learning for Physiologically-Based Pharmacokinetic Modeling in Dynamic PET. - Francesca De Benetti; Walter Simson; Magdalini Paschali; Hasan Sari; Axel Rominger; Kuangyu Shi; Nassir Navab; Thomas Wendler 001 (MICCAI (1), 2023)

Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans. - Michelle Xiao-Lin Foo; Seong Tae Kim 001; Magdalini Paschali; Leili Goli; Egon Burian; Marcus R. Makowski; Rickmer Braren; Nassir Navab; Thomas Wendler 001 (IEEE Access, 2023)

Investigating Pulse-Echo Sound Speed Estimation in Breast Ultrasound with Deep Learning. - Walter A. Simson; Magdalini Paschali; Vasiliki Sideri-Lampretsa; Nassir Navab; Jeremy J. Dahl (CoRR, 2023)

SOE: SO(3)-Equivariant 3D MRI Encoding. - Shizhe He; Magdalini Paschali; Jiahong Ouyang; Adnan Masood; Akshay Chaudhari; Ehsan Adeli-Mosabbeb (MLCN@MICCAI, 2024)

Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging. - Magdalini Paschali; Yu Hang Jiang; Spencer Siegel; Camila González; Kilian M. Pohl; Akshay Chaudhari; Qingyu Zhao (PRIME@MICCAI, 2024)

SINR: Spline-enhanced implicit neural representation for multi-modal registration. - Vasiliki Sideri-Lampretsa; Julian McGinnis; Huaqi Qiu; Magdalini Paschali; Walter Simson; Daniel Rueckert (MIDL, 2024)

CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation. - Zhihong Chen; Maya Varma; Jean-Benoit Delbrouck; Magdalini Paschali; Louis Blankemeier; Dave Van Veen; Jeya Maria Jose Valanarasu; Alaa Youssef; Joseph Paul Cohen; Eduardo Pontes Reis; Emily Bao Tsai; Andrew Johnston; et al. (CoRR, 2024)

Merlin: A Vision Language Foundation Model for 3D Computed Tomography. - Louis Blankemeier; Joseph Paul Cohen; Ashwin Kumar; Dave Van Veen; Syed Jamal Safdar Gardezi; Magdalini Paschali; Zhihong Chen; Jean-Benoit Delbrouck; Eduardo Pontes Reis; Cesar Truyts; Christian Bluethgen; Malte Engmann Kjeldskov Jensen; et al. (CoRR, 2024)

Foundation Models in Radiology: What, How, When, Why and Why Not. - Magdalini Paschali; Zhihong Chen; Louis Blankemeier; Maya Varma; Alaa Youssef; Christian Bluethgen; Curtis P. Langlotz; Sergios Gatidis; Akshay Chaudhari (CoRR, 2024)

Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM). - Zhongnan Fang; Andrew Johnston; Lina Cheuy; Hye Sun Na; Magdalini Paschali; Camila González; Bonnie A. Armstrong; Arogya Koirala; Derrick Laurel; Andrew Campion; Michael Iv; Akshay S. Chaudhari; et al. (CoRR, 2025)

Expert-level validation of AI-generated medical text with scalable language models. - Asad Aali; Vasiliki Bikia; Maya Varma; Nicole Chiou; Sophie Ostmeier; Arnav Singhvi; Magdalini Paschali; Ashwin Kumar; Andrew Johnston; Karimar Amador-Martinez; Eduardo Juan Perez Guerrero; Paola Naovi Cruz Rivera; et al. (CoRR, 2025)