Martin Lillholm

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Mads NielsenProfessor of Computer Science, University of CopenhagenDirección de correo verificada de diku.edu
Lewis D GriffinProfessor of Computer Science, University College LondonDirección de correo verificada de cs.ucl.ac.uk
Nico KarssemeijerProfessor of Computer Aided Diagnosis, Radboud University NijmegenDirección de correo verificada de radboudumc.nl
Christian IgelDepartment of Computer Science, University of CopenhagenDirección de correo verificada de diku.dk
Michiel G.J. KallenbergLaboratory of Geo-information Science and Remote Sensing, Wageningen UniversityDirección de correo verificada de wur.nl
Lauge SørensenFormerly Associated Professor at University of Copenhagen; Head of Development, Cerebriu A/SDirección de correo verificada de diku.dk
Akshay PaiCerebriu A/S ,University of Copenhagen, Biomediq A/SDirección de correo verificada de cerebriu.com
Joselene MarquesMachine Learning Engineering Manager at WorkdayDirección de correo verificada de workday.com
John Paulin HansenProfessor, Technical University of DenmarkDirección de correo verificada de dtu.dk
Emilie MøllenbachIT UniversityDirección de correo verificada de itu.dk
Jon SporringUniversity of CopenhagenDirección de correo verificada de di.ku.dk
Morten KarsdalProfessorDirección de correo verificada de nordicbioscience.com
Marco LoogRadboud UniversityDirección de correo verificada de ru.nl
Kim Steenstrup PedersenDepartment of computer science, University of CopenhagenDirección de correo verificada de diku.dk
Luc FlorackProfessor of Mathematical Image Analysis, Eindhoven University of TechnologyDirección de correo verificada de tue.nl

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Martin Lillholm

Associate Prof. Univiersity of Copenhagen, Senior Researcher, Biomediq

Dirección de correo verificada de biomediq.com

Medical Image Analysis Imaging Biomarkers


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Quaternions, interpolation and animation EB Dam, M Koch, M Lillholm Datalogisk Institut, Københavns Universitet, 1998	576	1998
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring M Kallenberg, K Petersen, M Nielsen, AY Ng, P Diao, C Igel, CM Vachon, ... IEEE transactions on medical imaging 35 (5), 1322-1331, 2016	501	2016
Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry L Sørensen, C Igel, A Pai, I Balas, C Anker, M Lillholm, M Nielsen, ... NeuroImage: Clinical 13, 470-482, 2017	161	2017
Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative EB Dam, M Lillholm, J Marques, M Nielsen Journal of Medical imaging 2 (2), 024001-024001, 2015	124	2015
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ... Scientific reports 11 (1), 3246, 2021	81	2021
Feature-based image analysis M Lillholm, M Nielsen, LD Griffin International Journal of Computer Vision 52, 73-95, 2003	79	2003
Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark M von Euler-Chelpin, M Lillholm, I Vejborg, M Nielsen, E Lynge Breast Cancer Research 21, 1-7, 2019	72	2019
Eye movements in gaze interaction E Møllenbach, JP Hansen, M Lillholm Journal of Eye Movement Research 6 (2), 2013	72	2013
Breast tissue segmentation and mammographic risk scoring using deep learning K Petersen, M Nielsen, P Diao, N Karssemeijer, M Lillholm Breast Imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan …, 2014	68	2014
An artificial intelligence–based mammography screening protocol for breast cancer: outcome and radiologist workload AD Lauritzen, A Rodríguez-Ruiz, MC von Euler-Chelpin, E Lynge, ... Radiology 304 (1), 41-49, 2022	65	2022
Single gaze gestures E Møllenbach, M Lillholm, A Gail, JP Hansen Proceedings of the 2010 symposium on eye-tracking research & applications …, 2010	57	2010
What do features tell about images? M Nielsen, M Lillholm Scale-Space and Morphology in Computer Vision: Third International …, 2001	57	2001
Basic image features (bifs) arising from approximate symmetry type LD Griffin, M Lillholm, M Crosier, J Van Sande Scale Space and Variational Methods in Computer Vision: Second International …, 2009	52	2009
Optimised region of interest selection EB Dam, M Nielsen, A Qazi, M Lillholm, DR Jørgenson US Patent 8,538,102, 2013	45	2013
Impact of adding breast density to breast cancer risk models: a systematic review BM Vilmun, I Vejborg, E Lynge, M Lillholm, M Nielsen, MB Nielsen, ... European journal of radiology 127, 109019, 2020	44	2020
Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study RR Winkel, M von Euler-Chelpin, M Nielsen, K Petersen, M Lillholm, ... BMC cancer 16, 1-12, 2016	44	2016
Single stroke gaze gestures E Møllenbach, JP Hansen, M Lillholm, AG Gale CHI'09 Extended Abstracts on Human Factors in Computing Systems, 4555-4560, 2009	44	2009
Screening mammography: benefit of double reading by breast density M Euler-Chelpin, M Lillholm, G Napolitano, I Vejborg, M Nielsen, E Lynge Breast cancer research and treatment 171, 767-776, 2018	41	2018
Mammographic texture resemblance generalizes as an independent risk factor for breast cancer M Nielsen, CM Vachon, CG Scott, K Chernoff, G Karemore, ... Breast Cancer Research 16, 1-8, 2014	38	2014
The combined effect of mammographic texture and density on breast cancer risk: a cohort study JOP Wanders, CH van Gils, N Karssemeijer, K Holland, M Kallenberg, ... Breast Cancer Research 20, 1-10, 2018	36	2018

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