Recovery of Surgical Workflow Without Explicit Models. - Seyed-Ahmad Ahmadi; Tobias Sielhorst; Ralf Stauder; Martin Horn; Hubertus Feußner; Nassir Navab (MICCAI (1), 2006)

Advanced planning and intra-operative validation for robot-assisted keyhole neurosurgery In ROBOCAST. - Seyed-Ahmad Ahmadi; Tassilo Klein; Nassir Navab; Ran Roth; Reuben R. Shamir; Leo Joskowicz; Elena De Momi; Giancarlo Ferrigno; Luca Antiga; Roberto Israel Foroni (ICAR, 2009)

MR in OR: First analysis of AR/VR visualization in 100 intra-operative Freehand SPECT acquisitions. - Asli Okur; Seyed-Ahmad Ahmadi; Ali Bigdelou; Thomas Wendler 001; Nassir Navab (ISMAR, 2011)

Midbrain Segmentation in Transcranial 3D Ultrasound for Parkinson Diagnosis. - Seyed-Ahmad Ahmadi; Maximilian Baust; Athanasios Karamalis; Annika Plate; Kai Boetzel; Tassilo Klein; Nassir Navab (MICCAI (3), 2011)

Rigid US-MRI Registration Through Segmentation of Equivalent Anatomic Structures - A Feasibility Study using 3D Transcranial Ultrasound of the Midbrain. - Seyed-Ahmad Ahmadi; Tassilo Klein; Annika Plate; Kai Boetzel; Nassir Navab (Bildverarbeitung für die Medizin, 2012)

Ultrasound bone detection using patient-specific CT prior. - Julian Beitzel; Seyed-Ahmad Ahmadi; Athanasios Karamalis; Wolfgang Wein; Nassir Navab (EMBC, 2012)

Detection of Substantia Nigra Echogenicities in 3D Transcranial Ultrasound for Early Diagnosis of Parkinson Disease. - Olivier Pauly; Seyed-Ahmad Ahmadi; Annika Plate; Kai Boetzel; Nassir Navab (MICCAI (3), 2012)

Frangi Goes US : Multiscale Tubular Structure Detection Adapted to 3D Ultrasound. - Paulo Waelkens; Seyed-Ahmad Ahmadi; Nassir Navab (MICCAI (1), 2012)

Statistical modeling and recognition of surgical workflow. - Nicolas Padoy; Tobias Blum; Seyed-Ahmad Ahmadi; Hubertus Feußner; Marie-Odile Berger; Nassir Navab (Medical Image Anal., 2012)

Learning from Multiple Experts with Random Forests: Application to the Segmentation of the Midbrain in 3D Ultrasound. - Pierre Chatelain; Olivier Pauly; Loïc Peter; Seyed-Ahmad Ahmadi; Annika Plate; Kai Bötzel; Nassir Navab (MICCAI (2), 2013)

Image Analysis Methods in Multi-View Transcranial 3D Ultrasound for Diagnosis of Neurological Movement-Disorders. - Seyed-Ahmad Ahmadi (2013)

Connectivity patterns of pallidal DBS electrodes in focal dystonia: A diffusion tensor tractography study. - Verena E. Rozanski; Christian Vollmar; João Paulo da Silva Cunha; Sérgio Miguel Neves Tafula; Seyed-Ahmad Ahmadi; Maximilian Patzig; Jan-Hinnerk Mehrkens; Kai Bötzel (NeuroImage, 2014)

Universal Hough dictionaries for object tracking. - Fausto Milletari; Wadim Kehl; Federico Tombari; Slobodan Ilic; Seyed-Ahmad Ahmadi; Nassir Navab (BMVC, 2015)

Robust Segmentation of Various Anatomies in 3D Ultrasound Using Hough Forests and Learned Data Representations. - Fausto Milletari; Seyed-Ahmad Ahmadi; Christine Kroll; Christoph Hennersperger; Federico Tombari; Amit Shah; Annika Plate; Kai Boetzel; Nassir Navab (MICCAI (2), 2015)

Patient-specific 3D Ultrasound Simulation Based on Convolutional Ray-tracing and Appearance Optimization. - Mehrdad Salehi; Seyed-Ahmad Ahmadi; Raphael Prevost; Nassir Navab; Wolfgang Wein (MICCAI (2), 2015)

3D transcranial ultrasound as a novel intra-operative imaging technique for DBS surgery: a feasibility study. - Seyed-Ahmad Ahmadi; Fausto Milletari; Nassir Navab; Madeleine Schuberth; Annika Plate; Kai Bötzel (Int. J. Comput. Assist. Radiol. Surg., 2015)

Multi-Scale Tubular Structure Detection in Ultrasound Imaging. - Christoph Hennersperger; Maximilian Baust; Paulo Waelkens; Athanasios Karamalis; Seyed-Ahmad Ahmadi; Nassir Navab (IEEE Trans. Medical Imaging, 2015)

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. - Fausto Milletari; Nassir Navab; Seyed-Ahmad Ahmadi (3DV, 2016)

Coupling Convolutional Neural Networks and Hough Voting for Robust Segmentation of Ultrasound Volumes. - Christine Kroll; Fausto Milletari; Nassir Navab; Seyed-Ahmad Ahmadi (GCPR, 2016)

Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields. - Patrick Ferdinand Christ; Mohamed Ezzeldin A. Elshaer; Florian Ettlinger; Sunil Tatavarty; Marc Bickel; Patrick Bilic; Markus Rempfler; Marco Armbruster; Felix Hofmann; Melvin D'Anastasi; Wieland H. Sommer; Seyed-Ahmad Ahmadi; et al. (MICCAI (2), 2016)

Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography. - Olivier Bernard 001; Johan G. Bosch; Brecht Heyde; Martino Alessandrini; Daniel Barbosa 001; Sorina Camarasu-Pop; Frederic Cervenansky; Sébastien Valette; Oana Mirea; Michel Bernier; Pierre-Marc Jodoin; Jaime Santo Domingos; et al. (IEEE Trans. Medical Imaging, 2016)

Diabetes60 - Inferring Bread Units From Food Images Using Fully Convolutional Neural Networks. - Patrick Ferdinand Christ; Sebastian Schlecht; Florian Ettlinger; Felix Grün; Christoph Heinle; Sunil Tatavarty; Seyed-Ahmad Ahmadi; Klaus Diepold; Bjoern H. Menze (ICCV Workshops, 2017)

SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D Convolutional Neural Networks. - Patrick Ferdinand Christ; Florian Ettlinger; Georgios Kaissis; Sebastian Schlecht; Freba Ahmaddy; Felix Grün; Alexander Valentinitsch; Seyed-Ahmad Ahmadi; Rickmer Braren; Bjoern H. Menze (ISBI, 2017)

Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks. - Patrick Ferdinand Christ; Florian Ettlinger; Felix Grün; Mohamed Ezzeldin A. Elshaer; Jana Lipková; Sebastian Schlecht; Freba Ahmaddy; Sunil Tatavarty; Marc Bickel; Patrick Bilic; Markus Rempfler; Felix Hofmann; et al. (CoRR, 2017)

Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound. - Fausto Milletari; Seyed-Ahmad Ahmadi; Christine Kroll; Annika Plate; Verena E. Rozanski; Juliana Maiostre; Johannes Levin; Olaf Dietrich; Birgit Ertl-Wagner; Kai Bötzel; Nassir Navab (Comput. Vis. Image Underst., 2017)

A diffusion-based connectivity map of the GPi for optimised stereotactic targeting in DBS. - Nádia Moreira da Silva; Seyed-Ahmad Ahmadi; Sérgio Miguel Neves Tafula; João Paulo da Silva Cunha; Kai Bötzel; Christian Vollmar; Verena E. Rozanski (NeuroImage, 2017)

Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion. - Gerome Vivar; Andreas Zwergal; Nassir Navab; Seyed-Ahmad Ahmadi (GRAIL/Beyond-MIC@MICCAI, 2018)

Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning. - Atanas Mirchev; Seyed-Ahmad Ahmadi (CoRR, 2018)

InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction. - Anees Kazi; Shayan Shekarforoush; S. Arvind Krishna; Hendrik Burwinkel; Gerome Vivar; Karsten Kortüm; Seyed-Ahmad Ahmadi; Shadi Albarqouni; Nassir Navab (IPMI, 2019)

Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph Networks. - Hendrik Burwinkel; Anees Kazi; Gerome Vivar; Shadi Albarqouni; Guillaume Zahnd; Nassir Navab; Seyed-Ahmad Ahmadi (MICCAI (6), 2019)

Graph Convolution Based Attention Model for Personalized Disease Prediction. - Anees Kazi; Shayan Shekarforoush; S. Arvind Krishna; Hendrik Burwinkel; Gerome Vivar; Benedikt Wiestler; Karsten Kortüm; Seyed-Ahmad Ahmadi; Shadi Albarqouni; Nassir Navab (MICCAI (4), 2019)

Stabilizing Inputs to Approximated Nonlinear Functions for Inference with Homomorphic Encryption in Deep Neural Networks. - Moustafa AboulAtta; Matthias Ossadnik; Seyed-Ahmad Ahmadi (CoRR, 2019)

Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets. - Gerome Vivar; Hendrik Burwinkel; Anees Kazi; Andreas Zwergal; Nassir Navab; Seyed-Ahmad Ahmadi (CoRR, 2019)

Cloud Deployment of High-Resolution Medical Image Analysis With TOMAAT. - Fausto Milletari; Johann Frei; Moustafa AboulAtta; Gerome Vivar; Seyed-Ahmad Ahmadi (IEEE J. Biomed. Health Informatics, 2019)

Decision Support for Intoxication Prediction Using Graph Convolutional Networks. - Hendrik Burwinkel; Matthias Keicher; David Bani-Harouni; Tobias Zellner; Florian Eyer; Nassir Navab; Seyed-Ahmad Ahmadi (MICCAI (2), 2020)

Domain-Specific Loss Design for Unsupervised Physical Training: A New Approach to Modeling Medical ML Solutions. - Hendrik Burwinkel; Holger Matz; Stefan Saur; Christoph Hauger; Ayse Mine Evren; Nino Hirnschall; Oliver Findl; Nassir Navab; Seyed-Ahmad Ahmadi (MICCAI (2), 2020)

Latent-Graph Learning for Disease Prediction. - Luca Cosmo; Anees Kazi; Seyed-Ahmad Ahmadi; Nassir Navab; Michael M. Bronstein (MICCAI (2), 2020)

Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time. - Gerome Vivar; Kamilia Mullakaeva; Andreas Zwergal; Nassir Navab; Seyed-Ahmad Ahmadi (MICCAI (2), 2020)

Latent Patient Network Learning for Automatic Diagnosis. - Luca Cosmo; Anees Kazi; Seyed-Ahmad Ahmadi; Nassir Navab; Michael M. Bronstein (CoRR, 2020)

Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC). - Gerome Vivar; Anees Kazi; Hendrik Burwinkel; Andreas Zwergal; Nassir Navab; Seyed-Ahmad Ahmadi (CoRR, 2020)

Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification. - Gerome Vivar; Anees Kazi; Hendrik Burwinkel; Andreas Zwergal; Nassir Navab; Seyed-Ahmad Ahmadi (Artif. Intell. Medicine, 2021)

Metabolic connectivity-based single subject classification by multi-regional linear approximation in the rat. - Maximilian Grosch; Leonie Beyer; Magdalena Lindner; Lena Kaiser; Seyed-Ahmad Ahmadi; Anna Stockbauer; Peter Bartenstein; Marianne Dieterich; Matthias Brendel; Andreas Zwergal; Sibylle Ziegler (NeuroImage, 2021)

Training β-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder. - Jianning Li 002; Jana Fragemann; Seyed-Ahmad Ahmadi; Jens Kleesiek; Jan Egger (MAD@MICCAI, 2022)

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. - Kamilia Mullakaeva; Luca Cosmo; Anees Kazi; Seyed-Ahmad Ahmadi; Nassir Navab; Michael M. Bronstein (CoRR, 2022)

Physics-aware learning and domain-specific loss design in ophthalmology. - Hendrik Burwinkel; Holger Matz; Stefan Saur; Christoph Hauger; Michael Trost; Nino Hirnschall; Oliver Findl; Nassir Navab; Seyed-Ahmad Ahmadi (Medical Image Anal., 2022)

Persistent horizontal and vertical, MR-induced nystagmus in resting state Human Connectome Project data. - Cammille C. Go; Huseyin O. Taskin; Seyed-Ahmad Ahmadi; Giulia Frazzetta; Laura Cutler; Saguna Malhotra; Jessica I. W. Morgan; Virginia L. Flanagin; Geoffrey Karl Aguirre (NeuroImage, 2022)

Transformers Pay Attention to Convolutions Leveraging Emerging Properties of ViTs by Dual Attention-Image Network. - Yousef Yeganeh; Azade Farshad; Peter Weinberger; Seyed-Ahmad Ahmadi; Ehsan Adeli 001; Nassir Navab (ICCV (Workshops), 2023)

DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation. - Yousef Yeganeh; Azade Farshad; Peter Weinberger; Seyed-Ahmad Ahmadi; Ehsan Adeli 001; Nassir Navab (CoRR, 2023)

Differentiable Graph Module (DGM) for Graph Convolutional Networks. - Anees Kazi; Luca Cosmo; Seyed-Ahmad Ahmadi; Nassir Navab; Michael M. Bronstein (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Open-source skull reconstruction with MONAI. - Jianning Li 002; André Ferreira; Behrus Puladi; Victor Alves; Michael Kamp; Moon S. Kim 002; Felix Nensa; Jens Kleesiek; Seyed-Ahmad Ahmadi; Jan Egger (SoftwareX, 2023)

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. - Kamilia Zaripova; Luca Cosmo; Anees Kazi; Seyed-Ahmad Ahmadi; Michael M. Bronstein; Nassir Navab (Medical Image Anal., 2023)