Erik B. Dam

49 papers A* 1B 5Journal 33Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Algorithmic Simplification of Neural Networks with Mosaic-of-Motifs.
CoRR
Pedram Bakhtiarifard, Tong Chen, Jonathan Wenshøj, Erik B. Dam, Raghavendra Selvan
2026 J jnl
How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI.
CoRR
Sophia N. Wilson, Sebastian Mair, Mophat Okinyi, Erik B. Dam, Janin Koch, Raghavendra Selvan
2026 J jnl
deCIFer: Crystal Structure Prediction from Powder Diffraction Data using Autoregressive Language Models.
Trans. Mach. Learn. Res.
Frederik L. Johansen, Ulrik Friis-Jensen, Erik B. Dam, Kirsten M. Ø. Jensen, Rocío Mercado, Raghavendra Selvan
2025 — conf
PePR: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning.
NLDL
Raghavendra Selvan, Bob Pepin, Christian Igel, Gabrielle Samuel, Erik B. Dam
2024 J jnl
A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation.
J. Open Source Softw.
Frederik L. Johansen, Andy S. Anker, Ulrik Friis-Jensen, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan
2024 A* conf
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning.
KDD
Ulrik Friis-Jensen, Frederik L. Johansen, Andy S. Anker, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan
2024 J jnl
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning.
CoRR
Ulrik Friis-Jensen, Frederik L. Johansen, Andy S. Anker, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan
2024 J jnl
Equity through Access: A Case for Small-scale Deep Learning.
CoRR
Raghavendra Selvan, Bob Pepin, Christian Igel, Gabrielle Samuel, Erik B. Dam
2024 J jnl
Fully Automated Tumor Segmentation for Brain MRI data using Multiplanner UNet.
CoRR
Sumit Pandey, Satyasaran Changdar, Mathias Perslev, Erik B. Dam
2023 — conf
Advancing Kidney, Kidney Tumor, Cyst Segmentation: A Multi-Planner U-Net Approach for the KiTS23 Challenge.
KiTS@MICCAI
Sumit Pandey, Toshali, Mathias Perslev, Erik B. Dam
2023 — conf
Comprehensive Multimodal Segmentation in Medical Imaging: Combining YOLOv8 with SAM and HQ-SAM Models.
ICCV (Workshops)
Sumit Pandey, Kuan-Fu Chen, Erik B. Dam
2023 J jnl
Comprehensive Multimodal Segmentation in Medical Imaging: Combining YOLOv8 with SAM and HQ-SAM Models.
CoRR
Sumit Pandey, Kuan-Fu Chen, Erik B. Dam
2023 — conf
Operating Critical Machine Learning Models in Resource Constrained Regimes.
MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI
Raghavendra Selvan, Julian Schön, Erik B. Dam
2023 J jnl
Operating critical machine learning models in resource constrained regimes.
CoRR
Raghavendra Selvan, Julian Schön, Erik B. Dam
2023 J jnl
The Liver Tumor Segmentation Benchmark (LiTS).
Medical Image Anal.
Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland H. Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Miriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Grün, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz K. Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John S. Lowengrub, Jun Ma, Klaus H. Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Manuel Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern H. Menze
2022 — conf
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis.
MICCAI (5)
Raghavendra Selvan, Nikhil Bhagwat, Lasse F. Wolff Anthony, Benjamin Kanding, Erik B. Dam
2022 J jnl
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis.
CoRR
Raghavendra Selvan, Nikhil Bhagwat, Lasse F. Wolff Anthony, Benjamin Kanding, Erik B. Dam
2021 J jnl
Fully automated quality control of rigid and affine registrations of T1w and T2w MRI in big data using machine learning.
Comput. Biol. Medicine
Sudhakar Tummala, Venkata Sainath Gupta Thadikemalla, Barbara A. K. Kreilkamp, Erik B. Dam, Niels K. Focke
2021 J jnl
Patch-based medical image segmentation using Quantum Tensor Networks.
CoRR
Raghavendra Selvan, Erik B. Dam, Søren Alexander Flensborg, Jens Petersen
2021 J jnl
Reply to Roemer and Guermazi: Early biochemical changes on MRI can predict risk of symptomatic progression.
Proc. Natl. Acad. Sci. USA
Shinjini Kundu, Beth G. Ashinsky, Mustapha Bouhrara, Erik B. Dam, Shadpour Demehri, Mohammad Shifat-E.-Rabbi, Richard G. Spencer, Kenneth L. Urish, Gustavo K. Rohde
2021 — conf
Segmenting Two-Dimensional Structures with Strided Tensor Networks.
IPMI
Raghavendra Selvan, Erik B. Dam, Jens Petersen
2021 J jnl
Segmenting two-dimensional structures with strided tensor networks.
CoRR
Raghavendra Selvan, Erik B. Dam, Jens Petersen
2020 J jnl
Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning.
Proc. Natl. Acad. Sci. USA
Shinjini Kundu, Beth G. Ashinsky, Mustapha Bouhrara, Erik B. Dam, Shadpour Demehri, Mohammad Shifat-E.-Rabbi, Richard G. Spencer, Kenneth L. Urish, Gustavo K. Rohde
2020 J jnl
Locally orderless tensor networks for classifying two- and three-dimensional medical images.
CoRR
Raghavendra Selvan, Silas Nyboe Ørting, Erik B. Dam
2020 J jnl
Lung Segmentation from Chest X-rays using Variational Data Imputation.
CoRR
Raghavendra Selvan, Erik B. Dam, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai
2020 J jnl
Multi-layered tensor networks for image classification.
CoRR
Raghavendra Selvan, Silas Nyboe Ørting, Erik B. Dam
2020 — conf
Tensor Networks for Medical Image Classification.
MIDL
Raghavendra Selvan, Erik B. Dam
2020 J jnl
Tensor Networks for Medical Image Classification.
CoRR
Raghavendra Selvan, Erik B. Dam
2020 J jnl
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset.
CoRR
Arjun D. Desai, Francesco Calivá, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew A. Torigian, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari
2019 J jnl
Muscle fibre morphology and microarchitecture in cerebral palsy patients obtained by 3D synchrotron X-ray computed tomography.
Comput. Biol. Medicine
Leise Borg, Jon Sporring, Erik B. Dam, Vedrana Andersen Dahl, Tim B. Dyrby, Robert Feidenhans'l, Anders B. Dahl, Jessica Pingel
2017 — ch.
Characterization of Errors in Deep Learning-Based Brain MRI Segmentation.
Deep Learning for Medical Image Analysis
Akshay Pai, Yuan-Ching Teng, Joseph Blair, Michiel Kallenberg, Erik B. Dam, Stefan Sommer, Christian Igel, Mads Nielsen
2017 J jnl
Simple Methods for Scanner Drift Normalization Validated for Automatic Segmentation of Knee Magnetic Resonance Imaging - with data from the Osteoarthritis Initiative.
CoRR
Erik B. Dam
2014 J jnl
Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI.
BMC Medical Imaging
Lene Lillemark, Lauge Sørensen, Akshay Pai, Erik B. Dam, Mads Nielsen
2013 — conf
Cube propagation for focal brain atrophy estimation.
ISBI
Akshay Pai, Lauge Sørensen, Sune Darkner, Peter Mysling, Dan R. Jørgensen, Erik B. Dam, Martin Lillholm, Joonmi Oh, Gennan Chen, Joyce Suhy, Jon Sporring, Mads Nielsen
2013 — conf
Femoral cartilage segmentation in Knee MRI scans using two stage voxel classification.
EMBC
Adhish Prasoon, Christian Igel, Marco Loog, François Lauze, Erik B. Dam, Mads Nielsen
2013 J jnl
Linear feature selection in texture analysis - A PLS based method.
Mach. Vis. Appl.
Joselene Marques, Christian Igel, Martin Lillholm, Erik B. Dam
2013 B conf
Morphometric connectivity analysis to distinguish normal, mild cognitive impaired, and Alzheimer subjects based on brain MRI.
Image Processing
Lene Lillemark, Lauge Sørensen, Peter Mysling, Akshay Pai, Erik B. Dam, Mads Nielsen
2013 J jnl
Predicting knee cartilage loss using adaptive partitioning of cartilage thickness maps.
Comput. Biol. Medicine
Dan R. Jørgensen, Erik B. Dam, Martin Lillholm
2012 J jnl
Automatic Quantification of Tibio-Femoral Contact Area and Congruity.
IEEE Trans. Medical Imaging
Sudhakar Tummala, Mads Nielsen, Martin Lillholm, Claus Christiansen, Erik B. Dam
2012 J jnl
Automatic analysis of trabecular bone structure from knee MRI.
Comput. Biol. Medicine
Joselene Marques, Rabia Granlund, Martin Lillholm, Paola Pettersen, Erik B. Dam
2012 J jnl
Distribution, Size, and Shape of Abdominal Aortic Calcified Deposits and Their Relationship to Mortality in Postmenopausal Women.
Int. J. Biomed. Imaging
Melanie Ganz, Marleen de Bruijne, Erik B. Dam, Paola Pettersen, Morten Asser Karsdal, Claus Christiansen, Mads Nielsen
2011 J jnl
Maximum a Posteriori Estimation of Linear Shape Variation With Application to Vertebra and Cartilage Modeling.
IEEE Trans. Medical Imaging
Alessandro Crimi, Martin Lillholm, Mads Nielsen, Anarta Ghosh, Marleen de Bruijne, Erik B. Dam, Jon Sporring
2010 J jnl
A framework for optimizing measurement weight maps to minimize the required sample size.
Medical Image Anal.
Arish A. Qazi, Dan R. Jørgensen, Martin Lillholm, Marco Loog, Mads Nielsen, Erik B. Dam
2010 B conf
Surface smoothness: cartilage biomarkers for knee OA beyond the radiologist.
Image Processing
Sudhakar Tummala, Erik B. Dam
2008 B conf
A variational method for automatic localization of the most pathological ROI in the knee cartilage.
Image Processing
Arish A. Qazi, Erik B. Dam, Marco Loog, Mads Nielsen, François Lauze, Claus Christiansen
2008 J jnl
Automatic shape model building based on principal geodesic analysis bootstrapping.
Medical Image Anal.
Erik B. Dam, P. Thomas Fletcher, Stephen M. Pizer
2008 J jnl
Efficient Segmentation by Sparse Pixel Classification.
IEEE Trans. Medical Imaging
Erik B. Dam, Marco Loog
2007 B conf
Automatic detection of diseased regions in knee cartilage.
Image Processing
Arish A. Qazi, Erik B. Dam, Ole Fogh Olsen, Mads Nielsen, Claus Christiansen
2006 B conf
Semi-automatic knee cartilage segmentation.
Image Processing
Erik B. Dam, Jenny Folkesson, Paola Pettersen, Claus Christiansen