Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Christoph Baur"'
Publikováno v:
Journal of Urban Mobility, Vol 1, Iss , Pp 100001- (2021)
The introduction of shared autonomous electric vehicles (SAEVs) brings along many advantages. Most of these advantages can be achieved when SAEVs are offered as on demand services by fleet operators. However, autonomous mobility on demand (AMoD) will
Externí odkaz:
https://doaj.org/article/50ced7ef9ccb46eeb2aa1e1bb76ae2c2
Publikováno v:
ISBI
Autoencoder-based approaches for Unsupervised Anomaly Detection (UAD) in brain MRI have recently gained a lot of attention and have shown promising performance. However, brain MR images are particularly complex and require large model capacity for le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc26e41628ec25afa6a4f417775edefa
https://doi.org/10.1109/isbi45749.2020.9098686
https://doi.org/10.1109/isbi45749.2020.9098686
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597122
MICCAI (2)
MICCAI (2)
Recently, it has been shown that CycleGANs are masters of steganography. They cannot only learn reliable mappings between two distributions without calling for paired training data, but can effectively hide information unseen during training in mappi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbfd2c51c94785d107ba5a7d60a0af61
https://doi.org/10.1007/978-3-030-59713-9_69
https://doi.org/10.1007/978-3-030-59713-9_69
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597184
MICCAI (4)
MICCAI (4)
Brain pathologies can vary greatly in size and shape, ranging from few pixels (i.e. MS lesions) to large, space-occupying tumors. Recently proposed Autoencoder-based methods for unsupervised anomaly segmentation in brain MRI have shown promising perf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::644b833216653acbc83a46569e581644
https://doi.org/10.1007/978-3-030-59719-1_54
https://doi.org/10.1007/978-3-030-59719-1_54
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery. 14:291-300
Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::309727d03722d8bb778ada5a40b9f480
https://doi.org/10.1007/s11548-018-1874-8
https://doi.org/10.1007/s11548-018-1874-8
Publikováno v:
Journal of Urban Mobility, Vol 1, Iss, Pp 100001-(2021)
The introduction of shared autonomous electric vehicles (SAEVs) brings along many advantages. Most of these advantages can be achieved when SAEVs are offered as on demand services by fleet operators. However, autonomous mobility on demand (AMoD) will
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4aaf37d385907369ec3e486642b6ca29
https://doi.org/10.1016/j.urbmob.2021.100001
https://doi.org/10.1016/j.urbmob.2021.100001
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783030117221
BrainLes@MICCAI (1)
BrainLes@MICCAI (1)
Reliably modeling normality and differentiating abnormal appearances from normal cases is a very appealing approach for detecting pathologies in medical images. A plethora of such unsupervised anomaly detection approaches has been made in the medical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::958ee3c147a646253ed696fc548a4332
https://doi.org/10.1007/978-3-030-11723-8_16
https://doi.org/10.1007/978-3-030-11723-8_16
Autor:
Nassir Navab, Benedikt Wiestler, Christoph Baur, Shadi Albarqouni, Claus Zimmer, Mark Muehlau
Publikováno v:
Radiol Artif Intell
PURPOSE: To develop an unsupervised deep learning model on MR images of normal brain anatomy to automatically detect deviations indicative of pathologic states on abnormal MR images. MATERIALS AND METHODS: In this retrospective study, spatial autoenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d41c22fa46f53d20c6ff7dc7fa367b8d
https://doi.org/10.1148/ryai.2021190169
https://doi.org/10.1148/ryai.2021190169
Publikováno v:
Med. Image Anal. 69:101952 (2021)
Deep unsupervised representation learning has recently led to new approaches in the field of Unsupervised Anomaly Detection (UAD) in brain MRI. The main principle behind these works is to learn a model of normal anatomy by learning to compress and re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9218d54c0db8dc22f018d065d9ac920
https://doi.org/10.1016/j.media.2020.101952
https://doi.org/10.1016/j.media.2020.101952
Autor:
Stefanie Demirci, Shadi Albarqouni, Nassir Navab, Vasileios Belagiannis, Christoph Baur, Felix Achilles
Publikováno v:
IEEE transactions on medical imaging 35(5), 1313-1321 (2016). doi:10.1109/TMI.2016.2528120
The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3631a7c37da4911fbd4d8d41bddcea4
https://doi.org/10.1109/tmi.2016.2528120
https://doi.org/10.1109/tmi.2016.2528120