Publikationen | Institute of Medical Informatics

MIDL 2021

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

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2015

Oktay O., Schuh A., Rajchl M., Keraudren K., Gomez A., Heinrich M.P., Penney G., Rueckert D.
Structured Decision Forests For Multi-modal Ultrasound Image Registration
In: Navab N., Hornegger J., Wells W., Frangi A.F. (eds.), 18th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, Munich, Lecture Notes in Computer Science, Springer, Berlin, LNCS Vol. 9350, 363-371, 2015

2016

Heinrich M.P., Oktay O.
Accurate Intervertebral Disc Localisation and Segmentation in MRI Using Vantage Point Hough Forests and Multi-atlas Fusion
In: International Workshop on Computational Methods and Clinical Applications for Spine Imaging, Springer, Cham, 77-84, 2016

2017

Heinrich M.P., Oktay O.
BRIEFnet: Deep Pancreas Segmentation Using Binary Sparse Convolutions
In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, Cham, 329-337, 2017

Oktay O., Bai W., Guerrero R., Rajchl M., de Marvao A., O’Regan D.P., Cook S.A., Heinrich M.P., Glocker B., Rueckert D.
Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images
IEEE Transactions on Medical Imaging, IEEE, 36, 1, 332-342, 2017

2018

Heinrich M.P., Oktay O.
Exploring Sparsity in CNNs for Medical Image Segmentation BRIEFnet
In: Maier A., Deserno T.M., Handels H., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2018, Erlangen, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 40-41, 2018

Heinrich M.P., Oktay O., Bouteldja N.
OBELISK – One Kernel to Solve Nearly Everything:Unified 3D Binary Convolutions for Image Analysis
In: Conference on Medical Imaging with Deep Learning (MIDL 2018), 2018

Heinrich M.P., Blendowski M., Oktay O.
TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions
International Journal of Computer Assisted Radiology and Surgery, 13, 9, 1311-1320, 2018

Oktay O., Ferrante E., Kamnitsas K., Heinrich M.P., Bai W., Caballero J., Cook S.A., de Marvao A., Dawes T., O'Regan D.P. et al.
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation
IEEE Transactions on Medical Imaging, 37, 2, 384-395, 2018

Oktay O., Schlemper J., Folgoc L.L., Lee M., Heinrich M.P., Misawa K., Mori K., McDonagh S., Hammerla N.Y., Kainz B. et al.
Attention U-Net: Learning Where to Look for the Pancreas
In: Conference on Medical Imaging with Deep Learning (MIDL 2018), 2018

Tanno R., Makropoulos A., Arslan S., Oktay O., Mischkewitz S., Al-Noor F., Oppenheimer J., Mandegaran R., Kainz B., Heinrich M.P.
AutoDVT: Joint Real-Time Classification for Vein Compressibility Analysis in Deep Vein Thrombosis Ultrasound Diagnostics
In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, LNCS, 11071, 905-912, 2018

2019

Heinrich M.P., Oktay O., Bouteldja N.
OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions
Medical Image Analysis, 54, 1-9, 2019

Schlemper J., Oktay O., Schaap M., Heinrich M.P., Kainz B., Glocker B., Rueckert D.
Attention gated networks: Learning to leverage salient regions in medical images
Medical Image Analysis, 53, 197-207, 2019

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