Machine Learning for Medical Image Reconstruction 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings / edited by Nandinee Haq, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo.

Machine Learning for Medical Image Reconstruction 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2021, held in conjunction with MICCAI 2021, in October 2021. The workshop was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19...

Full description

Saved in:
Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Haq, Nandinee (Editor), Johnson, Patricia (Editor), Maier, Andreas (Editor), Würfl, Tobias (Editor), Yoo, Jaejun (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Series:LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; 12964.
Subjects:
Artificial intelligence.
Online Access: Full text (Wentworth users only)

MARC

LEADER 00000cam a22000005i 4500
001 w2648451
005 20231013143317.0
007 cr nn 008mamaa
008 210929s2021 sz | s |||| 0|eng d
020 |a 9783030885526  |9 978-3-030-88552-6 
024 7 |a 10.1007/978-3-030-88552-6  |2 doi 
035 |a (DE-He213)978-3-030-88552-6 
040 |d UtOrBLW 
049 |a WENN 
050 4 |a Q334-342 
072 7 |a UYQ  |2 bicssc 
072 7 |a COM004000  |2 bisacsh 
072 7 |a UYQ  |2 thema 
082 0 4 |a 006.3  |2 23 
245 0 0 |a Machine Learning for Medical Image Reconstruction  |h [electronic resource] :  |b 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /  |c edited by Nandinee Haq, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo. 
250 |a 1st ed. 2021. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2021. 
300 |a VIII, 142 pages 53 illustrations, 37 illustrations in color :  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;  |v 12964 
505 0 |a Deep Learning for Magnetic Resonance Imaging -- HyperRecon: Regularization-Agnostic CS-MRI Reconstruction with Hypernetworks -- Efficient Image Registration Network For Non-Rigid Cardiac Motion Estimation -- Evaluation of the robustness of learned MR image reconstruction to systematic deviations between training and test data for the models from the fastMRI challenge -- Self-Supervised Dynamic MRI Reconstruction -- A Simulation Pipeline to Generate Realistic Breast Images For Learning DCE-MRI Reconstruction -- Deep MRI Reconstruction with Generative Vision Transformers -- Distortion Removal and Deblurring of Single-Shot DWI MRI Scans -- One Network to Solve Them All: A Sequential Multi-Task Joint Learning Network Framework for MR Imaging Pipeline -- Physics-informed self-supervised deep learning reconstruction for accelerated rst-pass perfusion cardiac MRI -- Deep Learning for General Image Reconstruction -- Noise2Stack: Improving Image Restoration by Learning from Volumetric Data -- Real-time Video Denoising in Fluoroscopic Imaging -- A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution -- Semi- and Self-Supervised Multi-View Fusion of 3D Microscopy Images using Generative Adversarial Networks. 
520 |a This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2021, held in conjunction with MICCAI 2021, in October 2021. The workshop was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic. The 13 papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction. 
650 0 |a Artificial intelligence.  |0 sh 85008180  
700 1 |a Haq, Nandinee,  |e editor.  |1 https://orcid.org/0000-0002-1346-2779  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt  |0 nb2021012869 
700 1 |a Johnson, Patricia,  |e editor.  |0 (orcid)0000-0003-1547-9969  |1 https://orcid.org/0000-0003-1547-9969  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Maier, Andreas,  |e editor.  |0 (orcid)0000-0002-9550-5284  |1 https://orcid.org/0000-0002-9550-5284  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Würfl, Tobias,  |e editor.  |1 https://orcid.org/0000-0001-9086-0896  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt  |0 nb2021003765 
700 1 |a Yoo, Jaejun,  |e editor.  |0 (orcid)0000-0001-5252-9668  |1 https://orcid.org/0000-0001-5252-9668  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service)  |0 no2005046756 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783030885519 
776 0 8 |i Printed edition:  |z 9783030885533 
830 0 |a LNCS sublibrary.  |n SL 6,  |p Image processing, computer vision, pattern recognition, and graphics ;  |v 12964.  |0 no2007037053 
951 |a 2648451 
999 f f |i f1b11c05-0b03-57a6-a7a4-fe7a47216c76  |s be03a8a2-7dce-548f-aaf5-ccb6f347f4a3  |t 0 
952 f f |a Wentworth Institute of Technology  |b Main Campus  |c Wentworth Library  |d Ebooks  |t 0  |e Springer  |h Other scheme 
856 4 0 |t 0  |u https://ezproxywit.flo.org/login?qurl=https://doi.org/10.1007/978-3-030-88552-6  |y Full text (Wentworth users only) 

Similar Items