MIDL 2021

 
International Conference on
Medical Imaging with Deep Learning
5. bis 7. Juli 2021

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Lux P., Diesel J., Heinrich M.P.
2D Image Registration for Transforming Segmentation Masks within a Multi-Modal Camera Setup
In: Buzug T.M., Handels H., Klein S., Mertins A. (eds.), Student Conference 2019, Medical Engineering Science, Medical Informatics, Biomedical Engineering and Auditory Technology, Lübeck, Infinite Science Publishing, 129-132, 2019
Lucas C., Maier O., Heinrich M.P.
Shallow fully-connected neural networks for ischemic stroke-lesion segmentation in MRI
In: Maier-Hein K.H., Deserno T.M., Handels H., Tolxdorff T. (eds.), Bildverarbeitung in der Medizin 2017, Heidelberg, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 261-266, 2017
Lucas C., Schöttler J.J., Kemmling A., Aulmann L.F., Heinrich M.P.
Automatic Detection and Segmentation of the Acute Vessel Thrombus in Cerebral CT
In: Handels H., Deserno T.M., Maier A., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 74-79, 2019
Lucas C., Aulmann L.F., Kemmling A., Mamlouk A.M., Heinrich M.P.
Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes
In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2019, 69-79, 2020
Lucas C., Kemmling A., Madany Mamlouk A., Heinrich M.P.
Multi-scale neural network for automatic segmentation of ischemic strokes on acute perfusion images
In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, IEEE, 1118-1121, 2018
Lucas C., Aulmann L.F., Kemmling A., Mamlouk A.M., Heinrich M.P.
Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes
In: Tolxdorff T., Deserno T.M., Handels H., Maier A., Maier-Hein K.H., Palm C. (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 143, 2020
Lucas C., Kemmling A., Bouteldja N., Aulmann L.F., Madany Mamlouk A., Heinrich M.P.
Learning to Predict Ischemic Stroke Growth on Acute CT Perfusion Data by Interpolating Low-Dimensional Shape Representations
Frontiers in Neurology, 9, 989, 2018
Lübbe C., Friedrich B., Fudickar S., Hellmers S., Hein A.
Feature Based Random Forest Nurse Care Activity Recognition Using Accelerometer Data
In: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (UbiComp/ISWC '20 Adjunct), 2020
Abstract
Löffler B.S., Fudickar S., Herrmann C.S., Hein A.
Ein Blick in das Gehirn: Messung und Verbesserung der Fahrleistung älterer Autofahrender mit Hilfe von Neuroimaging und Elektrostimulation
In: Carolin Wienrich Thorsten Zander K.G. (ed.), Trends in Neuroergonomics, Berlin, 11. Berliner Werkstatt Mensch-Maschine-Systeme, Universitätsverlag der TU Berlin, 166-169, 2015
Abstract
Löffler B.S., Stecher H.I., Fudickar S., de Sordi D., Otto-Sobotka F., Hein A., Herrmann C.H.
Counteracting the Slowdown of Reaction Times in a Vigilance Experiment with 40-Hz Transcranial Alternating Current Stimulation
IEEE - Transactions on Neural Systems & Rehabilitation Engineering, 2018
Abstract
Löbe M., Ulrich H., Beger C., Bender T., Bauer C., Sax U., Ingenerf J., Winter A.
Improving Findability of Digital Assets in Research Data Repositories Using the W3C DCAT Vocabulary
Studies in Health Technology and Informatics, 290, 61-65, 2022
Lins C., Eckhoff D., Klausen A., Hellmers S., Hein A., Fudickar S.
Cardiopulmonary resuscitation quality parameters from motion capture data using Differential Evolution fitting of sinusoids
Applied Soft Computing, 2019
Abstract
Lins C., Fudickar S., Hein A.
SKAML: An XML Markup Language for Abstract Skeleton Definitions in the Context of Human Posture Assessments
In: Medical Informatics Europe, Gothenburg, Sweden, 2018
Abstract
Lins C., Fudickar S., Hein A.
OWAS inter-rater reliability
Applied Ergonomics, 93, 103357, 2021
Abstract
Lins C., Friedrich B., Hein A., Fudickar S.
An evolutionary approach to continuously estimate CPR quality parameters from a wrist-worn inertial sensor
Health and Technology, 161-173, 2022
Abstract
Lins C., Fudickar S., Hein A.
XML Skeleton Definitions for Human Posture Assessments
Studies in Health Technology and Informatics, 253, 225-229, 2018
Abstract
Lins C., Fudickar S., Gerka A., Hein A.
A Wearable Vibrotactile Interface for Unfavorable Posture Awareness Warning
In: in Proc. 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2018), Funchal - Madeira, Portugal, 2018
Abstract
Lins C., Klausen A., Fudickar S., Hellmers S., Lipprandt M., Röhrig R., Hein A.
Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves
In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, Funchal - Madeira, Portugal, SCITEPRESS - Science and Technology Publications, 665-670, 2018
Abstract
Linnepe D., Groppe S., Ingenerf J.
Nutzung von MEDLINE und MeSH für das Benchmarking von RDF-Speichersystemen
In: 54. GMDS-Jahrestagung, September 2009 in Essen, online-verfügbares Meeting-Abstract im GMS-Journal, 2009., 2009
Linder R., Theegarten D., Mayer S., Anhenn O., Ebsen M., Schwarze J., Neesen J., Sudhoff H., Pöppl S.J., Wagner M.
Der Einsatz eines Modifizierten Causal Index erleichtert die Interpretation des Antwortverhaltens eines mit Daten einer Whole-Body Plethysmographie an einem Knock Out Mausmodell trainierten Artifiziellen Neuronalen Netzwerks (ANN)
Atemw.-Lungenkrkh., 29(7), 340-343, 2003
Linder R., Pöppl S.J., Schönweiler R.
Psychoakustische Skalierung akustischer Heiserkeitsparameter einschließlich GNE mittels Künstlicher Neuronaler Netze
In: Gross M. (ed.), Aktuelle phoniatrisch-pädaudiologische Aspekte 2002/2003, Median-Verlag, Heidelberg, 85-89, 2002
Linder R., Dümbgen L., Wirtz S., Pöppl S.J.
Klassifikation von Signalen einer elektronischen Nase
Biomedizinische Technik / Biomedical Engineering, 45, 194-195, 2000
Linder R., Hoffmann A., Brunner R.
Prevalence of the Spondyloarthropathies in Patients with Uveitis
J Rheumatol, 31(11), 4Seiten, 2004
Linder R., Wrage J.-H., Beck F., Pöppl S.J.
aXess: Ein Autorentool für die Pflege von XML-Content
In: 49. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS) e.V., Innsbruck/Tirol, Tagungsband, 3Seiten, 2004
Linder R., Pöppl S.J.
About the Capabilities of Artificial Neural Networks in Body Composition Research
In: Sixth International Symposium “In Vivo Body Composition Studies”, Rome, Italy, Acta Diabetologica, 39, 133, 2002
Linder R.
Künstliche Neuronale Netze in der Medizin
Forum der Medizin-Dokumentation und Medizin-Informatik (mdi) , 5(4), 112-118, 2003
Linder R., Wrage J.-H., Schlichting S., Pöppl S.J.
aXess: an authoring tool for XML content management
e-learning & education (eleed), 2. Issue, 2005
Linder R., Wirtz. S., Pöppl S.J.
Speeding up Backpropagation Learning by the APROP Algorithm
In: Second International ICSC Symposium on Neural Computation, Berlin, Proceedings CD, 2000
Linder R., Dodt C., Kurowski V., Djonlagic H.
Vorteil eigenständiger Stationen
Deutsches Ärzteblatt , 26, 1490-1491, 2003
Linder R., Richards T., Wagner M.
Microarray Data classified by Artificial Neural Networks
Methods in molecular biology (Clifton, N.J.), 382, 345-72, 2007
Abstract
Linder R., Pöppl S.J.
ACMD: A Practical Tool for Automatic Neural Net Based Learning
In: Crespo J., Maojo V., Martin F. (eds.), Second International Symposium on Medical Data Analysis (ISMDA), Madrid, Lecture Notes in Computer Science, Medical Data Analysis, Springer Berlin Heidelberg, 2199, 168-173, 2001
Linder R., Dew D., Sudhoff H., Theegarten D., Remberger K., Pöppl S.J., Wagner M.
The 'Subsequent Artificial Neural Network' (SANN) Approach Might Bring More Classificatory Power to ANN-based DNA Microarray Analyses
Bioinformatics, 20, 18, 3544-3552, 2004
Linder R., Ingenerf J., Pöppl S.J.
Dokumentation und Kommunikation im Gesundheitswesen: eine Einführung
E-Learning Modul im Vertiefungsbereich "Natur und Technik" des Diplomstudiengangs „Gesundheitswissenschaften“ der University of Applied Sciences sowie im Verbundprojekt „Hochschulen für Gesundheit“, University of Applied Sciences, Hamburg, 2003
Linder R., Ingenerf J., Katalinic A., Thyen U., Schönweiler R.
Tracking Children for the Newborn Hearing Screening in Northern Germany
In: MEDINFO 2007, Brisbane, Australien, Proceedings of the 12th World Congress on Health (Medical) Informatics, Tagungs-CD1237-1250, 2007
Linder R., Pöppl S.J.
Food Quality Assurance Applying a Sophisticated Neural Network to Olfactory Signals
In: 6th Sensometrics, Dortmund, Tagungsband, 2002
Linder R., Dinser R., Wagner M., Krueger G.R.F., Hoffmann A.
Generation of classification criteria for chronic fatigue syndrome using an artificial neural network and traditional criteria set.
In vivo (Athens, Greece), 16, 1, 37-43, 2002
Abstract
Linder R., Zamelczyk-Pajewska M., Pöppl S.J., Kośmider J.
An Artificial Neural Network Is Capable of Predicting Odour Intensity
Pol J Environ Stud, 14(4), 477-481, 2005
Linder R., Pöppl S.J.
Backprop, RPROP, APROP: Searching for the best learning rule for an electronic nose
In: Fourth International Workshop 1999, Magdeburg, Neural Networks in Applications '99, 69-74, 1999
Linder R., Katalinic A., Thyen U., Schönweiler R.
UNHS-SH: ein multidisziplinärer Ansatz für das Neugeborenenhörscreening in Schleswig-Holstein. Aktuelle phoniatrisch-pädaudiologische Aspekte
In: 22. Wissenschaftliche Jahrestagung der Deutschen Gesellschaft für Phoniatrie und Pädaudiologie, 2005
Linder R., Reinhold-Keller E., Gross W.L.
Use of an artificial neural network to predict cancer development in patients with inflammatory myopathy: comment on the letter by Selva O'Callaghan et al.
Arthritis and rheumatism, 48, 4, 1168-9;authorreply1169-70, 2003
Linder R.
Lernstrategien zur automatisierten Anwendung künstlicher neuronaler Netzwerke in der Medizin
Logos, Berlin, 2006
Linder R., Pöppl S.J.
How to Automate Neural Net Based Learning
In: Perner P. (ed.), Second International Workshop MLDM 2001, Leipzig, Lecture Notes in Computer Science, Machine Learning and Data Mining in Pattern Recognition, Springer Berlin Heidelberg, 2123, 206-216, 2001
Linder R., Pöppl S.J.
A new neural network approach classifies olfactory signals with high accuracy
Food Quality and Preference, 14, 5-6, 435-440, 2003
Linder R., Mohamed E., Maiolo C., Pöppl S.J., De Lorenzo A.
Predicting Intracellular Water Compartment for Healthy Italiens Using Artificial Neural Network Analysis
In: Sixth International Symposium “In Vivo Body Composition Studies”, Rome, Italy, Acta Diabetologica, 39, 137, 2002
Linder R., Pöppl S.J.
Artificial Neural Networks for Classifying Olfactory Signals
Studies in health technology and informatics, 77, 1220-5, 2000
Abstract
Linder R., Albers A.E., Hess M., Pöppl S.J., Schönweiler R.
Artificial neural network-based classification to screen for dysphonia using psychoacoustic scaling of acoustic voice features.
Journal of voice : official journal of the Voice Foundation, 22, 2, 155-63, 2008
Abstract
Linder R., Geier J., Kölliker M.
Artificial neural networks, classification trees and regression: Which method for which customer?
Database Marketing & Customer Strategy Management, 11(4), 344-356, 2004
Linder R., Pöppl S.J.
Optimierung der Konvergenzgeschwindigkeit von Backpropagation
In: 20. DAGM Symposium, Stuttgart, Springer, Berlin u.a., 175-182, 1998
Linder R., Mohamed E.I., De Lorenzo A., Pöppl S.J.
The Capabilities of Artificial Neural Networks in Body Composition Research
Acta diabetologica, 40 Suppl 1, S9-14, 2003
Abstract
Linder R., König I.R., Weimar C., Diener H.C., Pöppl S.J., Ziegler A.
Two Models for Outcome Prediction - a Comparison of Logistic Regression and Neural Networks
Methods of information in medicine, 45, 5, 536-40, 2006
Abstract

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