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| 001 | 145540 | ||
| 005 | 20250522150104.0 | ||
| 020 | _ | _ | |a 978-3-030-00128-5 (print) |
| 020 | _ | _ | |a 978-3-030-00129-2 (electronic) |
| 024 | 7 | _ | |a 10.1007/978-3-030-00129-2_4 |2 doi |
| 024 | 7 | _ | |a 0302-9743 |2 ISSN |
| 024 | 7 | _ | |a 1611-3349 |2 ISSN |
| 037 | _ | _ | |a DZNE-2020-00874 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Dedmari, Muneer Ahmad |0 P:(DE-2719)2812572 |b 0 |u dzne |
| 111 | 2 | _ | |a Machine Learning for Medical Image Reconstruction |g MLMIR 2018 |c Granada |d 2018-09-16 - 2018-09-16 |w Spain |
| 245 | _ | _ | |a Complex Fully Convolutional Neural Networks for MR Image Reconstruction |
| 260 | _ | _ | |c 2018 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a Other |2 DataCite |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Book |0 PUB:(DE-HGF)3 |2 PUB:(DE-HGF) |m book |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1747918810_22615 |2 PUB:(DE-HGF) |x Other |
| 520 | _ | _ | |a Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image reconstruction employ real-valued operations and representations by treating complex valued k-space/spatial-space as real values. In this paper, we propose complex dense fully convolutional neural network (CDFNet) for learning to de-alias the reconstruction artifacts within undersampled MRI images. We fashioned a densely-connected fully convolutional block tailored for complex-valued inputs by introducing dedicated layers such as complex convolution, batch normalization, non-linearities etc. CDFNet leverages the inherently complex-valued nature of input k-space and learns richer representations. We demonstrate improved perceptual quality and recovery of anatomical structures through CDFNet in contrast to its real-valued counterparts. |
| 536 | _ | _ | |a 345 - Population Studies and Genetics (POF3-345) |0 G:(DE-HGF)POF3-345 |c POF3-345 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef Book Series, Journals: pub.dzne.de |
| 700 | 1 | _ | |a Conjeti, Sailesh |0 P:(DE-2719)2812477 |b 1 |u dzne |
| 700 | 1 | _ | |a Estrada Leon, Edgar Santiago |0 P:(DE-2719)2812449 |b 2 |u dzne |
| 700 | 1 | _ | |a Ehses, Philipp |0 P:(DE-2719)2812222 |b 3 |u dzne |
| 700 | 1 | _ | |a Stöcker, Tony |0 P:(DE-2719)2810538 |b 4 |u dzne |
| 700 | 1 | _ | |a Reuter, Martin |0 P:(DE-2719)2812134 |b 5 |u dzne |
| 773 | _ | _ | |a 10.1007/978-3-030-00129-2_4 |
| 856 | 4 | _ | |u https://link.springer.com/chapter/10.1007/978-3-030-00129-2_4 |
| 909 | C | O | |p VDB |o oai:pub.dzne.de:145540 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 0 |6 P:(DE-2719)2812572 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 1 |6 P:(DE-2719)2812477 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 2 |6 P:(DE-2719)2812449 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 3 |6 P:(DE-2719)2812222 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 4 |6 P:(DE-2719)2810538 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 5 |6 P:(DE-2719)2812134 |
| 913 | 1 | _ | |a DE-HGF |b Gesundheit |l Erkrankungen des Nervensystems |1 G:(DE-HGF)POF3-340 |0 G:(DE-HGF)POF3-345 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-300 |4 G:(DE-HGF)POF |v Population Studies and Genetics |x 0 |
| 914 | 1 | _ | |y 2018 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |d 2024-12-28 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2024-12-28 |
| 920 | 1 | _ | |0 I:(DE-2719)1040310 |k AG Reuter |l Artificial Intelligence in Medicine |x 0 |
| 920 | 1 | _ | |0 I:(DE-2719)1012001 |k AG Breteler |l Population Health Sciences |x 1 |
| 920 | 1 | _ | |0 I:(DE-2719)1013026 |k AG Stöcker |l MR Physics |x 2 |
| 980 | _ | _ | |a conf |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a book |
| 980 | _ | _ | |a I:(DE-2719)1040310 |
| 980 | _ | _ | |a I:(DE-2719)1012001 |
| 980 | _ | _ | |a I:(DE-2719)1013026 |
| 980 | _ | _ | |a UNRESTRICTED |
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