Zobrazeno 1 - 10
of 140
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
Autor:
Erhard Christoph Baur
Publikováno v:
Národní knihovna České republiky.
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
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
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
Autor:
Anirban Mukhopadhyay, Shadi Albarqouni, Christoph Baur, Bram van Ginneken, Nassir Navab, Arjan Kuijper, Salome Kazeminia
Publikováno v:
Artificial Intelligence in Medicine. 109:101938
Generative Adversarial Networks (GANs) and their extensions have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical image de-noising, reconstruction, segmentation, data simulation, dete
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