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2020

  • A. Rogalla and S. Lehmann and M. Neidhardt and J. Sprenger and M. Bengs and A. Schlaefer and S. Schupp (2020). Synthesizing Strategies for Needle Steering in Gelatin Phantoms. Models for Formal Analysis of Real Systems (MARS 2020) [Abstract] [doi] [www] [BibTex]

  • A. Rogalla and T. Kamph and U. Bulmann and K. Billerbeck and M. Blumreiter and S. Schupp (2020). Designing And Analyzing Open Application-Oriented Labs in Software-Verification Education. Annual Conference of European Society for Engineering Education (SEFI). Enschede (the Netherlands) 444-453. [Abstract] [BibTex]

  • D.B. Ellebrecht and S. Latus and A. Schlaefer and T. Keck and N. Gessert (2020). Towards an Optical Biopsy during Visceral Surgical Interventions. Visceral Medicine. [Abstract] [doi] [BibTex]

  • F. Behrendt and N. Gessert and A. Schlaefer (2020). Generalization of spatio-temporal deep learning for vision-based force estimation. Current Directions in Biomedical Engineering. 6 (1), 20200024. [Abstract] [doi] [www] [BibTex]

  • F. Griese AND S. Latus AND M. Schlüter AND M. Graeser AND M. Lutz AND A. Schlaefer AND T. Knopp (2020). In-Vitro MPI-guided IVOCT catheter tracking in real time for motion artifact compensation. PLOS ONE. 15 (3), e0230821. [Abstract] [doi] [www] [BibTex]

  • L. Bargsten AND A. Schlaefer (2020). SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing. International Journal of Computer Assisted Radiology and Surgery. 15 (9), 1427-1436. [Abstract] [doi] [www] [BibTex]

  • L. Bargsten and K. A. Riedl and T. Wissel and F. J. Brunner and K. Schaefers and J. Sprenger and M. Grass and S. Blankenberg and M. Seiffert and A. Schlaefer (2020). Tailored Methods for Segmentation of Intravascular Ultrasound Images via Convolutional Neural Networks. SPIE Medical Imaging Conference accepted. [BibTex]

  • M. Bengs and N. Gessert and A. Schlaefer (2020). A Deep Learning Approach for Motion Forecasting Using 4D OCT Data. International Conference on Medical Imaging with Deep Learning accepted. [Abstract] [www] [BibTex]

  • M. Bengs and N. Gessert and M. Schlüter and A. Schlaefer (2020). Spatio-Temporal Deep Learning Methods for Motion Estimation Using 4D OCT Image Data. International Journal of Computer Assisted Radiology and Surgery. 15 (6), 943-952. [Abstract] [doi] [www] [BibTex]

  • M. Bengs and N. Gessert and W. Laffers and D. Eggert and S. Westermann and N.A. Mueller and A.O.H. Gerstners and C. Betz and A. Schlaefer (2020). Spectral-spatial Recurrent-Convolutional Networks for In-Vivo Hyperspectral Tumor Type Classification. Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 Springer International Publishing: Cham 690-699. [Abstract] [BibTex]

  • M. Bengs and S. Westermann and N. Gessert and D. Eggert and A. O. H. Gerstner, N. A. Mueller and C. Betz and W. Laffers and A. Schlaefer (2020). Spatio-spectral deep learning methods for in-vivohyperspectral laryngeal cancer detection. SPIE Medical Imaging 2020: Computer-Aided Diagnosis in print. [BibTex]

  • M. Bengs and T. Gessert and A. Schlaefer (2020). 4D spatio-temporal convolutional networks for object position estimation in OCT volumes. Current directions in biomedical engineering. 6 (1), 20200001. [Abstract] [doi] [www] [BibTex]

  • M. Gromniak and M. Neidhardt and A. Heinemann and K. Püschel and A. Schlaefer (2020). Needle placement accuracy in CT-guided robotic post mortem biopsy. Current Directions in Biomedical Engineering. 6 (1), 20200031. [Abstract] [doi] [www] [BibTex]

  • M. Gromniak and N. Gessert and T. Saathoff and A. Schlaefer (2020). Needle tip force estimation by deep learning from raw spectral OCT data. International Journal of Computer Assisted Radiology and Surgery. 15 1699-1702. [Abstract] [doi] [www] [BibTex]

  • M. Neidhardt and M. Bengs and S. Latus and M. Schlüter and T. Saathoff and A. Schlaefer (2020). 4D Deep learning for real-time volumetric optical coherence elastography. International Journal of Computer Assisted Radiology and Surgery 2020 1861-6429. [Abstract] [doi] [www] [BibTex]

  • M. Neidhardt and M. Bengs and S. Latus and M. Schlüter and T. Saathoff and A. Schlaefer (2020). Deep Learning for High Speed Optical Coherence Elastography. IEEE International Symposium on Biomedical Imaging 1583-1586. [Abstract] [doi] [BibTex]

  • M. Neidhardt and N. Gessert and T. Gosau and J. Kemmling and S. Feldhaus and U. Schumacher and A. Schlaefer (2020). Force estimation from 4D OCT data in a human tumor xenograft mouse model. Current Directions in Biomedical Engineering. 6 (1), 20200022. [Abstract] [doi] [www] [BibTex]

  • M. Schlüter and L. Glandorf and J. Sprenger and M. Gromniak and M. Neidhardt and T. Saathoff and A. Schlaefer (2020). High-Speed Markerless Tissue Motion Tracking Using Volumetric Optical Coherence Tomography Images. IEEE International Symposium on Biomedical Imaging 1979-1982. [Abstract] [doi] [BibTex]

  • M. Schlüter and L. Glandorf and M. Gromniak and T. Saathoff and A. Schlaefer (2020). Concept for Markerless 6D Tracking Employing Volumetric Optical Coherence Tomography. Sensors. 20 (9), 2678. [Abstract] [doi] [BibTex]

  • M. Seemann and L. Bargsten and A. Schlaefer (2020). Data augmentation for computed tomography angiography via synthetic image generation and neural domain adaptation. Current Directions in Biomedical Engineering. 6 (1), 20200015. [Abstract] [doi] [www] [BibTex]

  • N. Gessert and A. Schlaefer (2020). Left Ventricle Quantification Using Direct Regression with Segmentation Regularization and Ensembles of Pretrained 2D and 3D CNNs. arXiv e-prints. Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges. STACOM@MICCAI 2019. Lecture Notes in Computer Science. 375-383. [Abstract] [doi] [www] [BibTex]

  • N. Gessert and J. Krüger and R. Opfer and A.-C. Ostwaldt and P. Manogaran and H. H. Kitzler and S. Schippling and A. Schlaefer (2020). Multiple Sclerosis Lesion Activity Segmentation with Attention-Guided Two-Path CNNs. Computerized Medical Imaging and Graphics. 84 (101772), [Abstract] [doi] [www] [BibTex]

  • N. Gessert and M. Bengs and A. Schlaefer (2020). Melanoma detection with electrical impedance spectroscopy and dermoscopy using joint deep learning models. SPIE Medical Imaging 2020 in print. [Abstract] [www] [BibTex]

  • N. Gessert and M. Bengs and J. Krüger and R. Opfer and A.-C. Ostwaldt and P. Manogaran and S. Schippling and A. Schlaefer (2020). 4D Deep Learning for Multiple-Sclerosis Lesion Activity Segmentation. Medical Imaging with Deep Learning accepted. [Abstract] [www] [BibTex]

  • N. Gessert and M. Bengs and M. Schlüter and A. Schlaefer (2020). Deep learning with 4D spatio-temporal data representations for OCT-based force estimation. Medical Image Analysis. 64 (101730), [Abstract] [doi] [www] [BibTex] [pmid]

  • N. Gessert and M. Nielsen and M. Shaikh and R. Werner and A. Schlaefer (2020). Skin lesion classification using ensembles of multi-resolution EfficientNets with meta data. MethodsX. 7 100864. [Abstract] [doi] [www] [BibTex]

  • N. Gessert and T. Sentker and F. Madesta and R. Schmitz and H. Kniep and I. Baltruschat and R. Werner and A. Schlaefer (2020). Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting. IEEE Transactions on Biomedical Engineering. 67 (2), 495-503. [Abstract] [doi] [www] [BibTex]

  • S. Gerlach and C. Fürweger and T. Hofmann and A. Schlaefer (2020). Multicriterial CNN based beam generation for robotic radiosurgery of the prostate. Current Directions in Biomedical Engineering. 6 (1), 20200030. [Abstract] [doi] [www] [BibTex]

  • S. Gerlach and C. Fürweger and T. Hofmann and A. Schlaefer (2020). Feasibility and analysis of CNN-based candidate beam generation for robotic radiosurgery. Medical Physics. 47 (9), 3806-3815. [Abstract] [doi] [www] [BibTex]

  • S. Latus and P. Breitfeld and M. Neidhardt and W. Reip and C. Zöllner and A. Schlaefer (2020). Boundary prediction during epidural punctures based on OCT relative motion analysis. EUR J ANAESTH. 2020 (Volume 37 | e-Supplement 58 | June 2020), [Abstract] [BibTex]

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