Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Hannah Strohm"'
Autor:
Amir Asif, Dongwoon Hyun, David Sinden, Ruud J. G. van Sloun, Sobhan Goudarzi, Muyinatu A. Lediju Bell, Sven Rothlubbers, Massimo Mischi, Hassan Rivaz, Yonina C. Eldar, Klaus Eickel, Alycen Wiacek, Jiaqi Huang, Hannah Strohm
Publikováno v:
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 68(12):9475029, 3466-3483. Institute of Electrical and Electronics Engineers
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 68(12):9475029, 3466-3483. Institute of Electrical and Electronics Engineers
Deep learning for ultrasound image formation is rapidly garnering research support and attention, quickly rising as the latest frontier in ultrasound image formation, with much promise to balance both image quality and display speed. Despite this pro
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery.
Purpose Computed tomography (CT) is widely used to identify anomalies in brain tissues because their localization is important for diagnosis and therapy planning. Due to the insufficient soft tissue contrast of CT, the division of the brain into anat
Publikováno v:
2022 IEEE International Ultrasonics Symposium (IUS).
Publikováno v:
2021 IEEE International Ultrasonics Symposium (IUS).
The quality of ultrasound plane wave imaging benefits from compounding multiple angle acquisitions to reconstruct an image. However, the acquisition of additional data lowers the frame rate and – in presence of motion – the data integrity. This w
Publikováno v:
2020 IEEE International Ultrasonics Symposium (IUS).
Classical ultrasound reconstruction applies model driven approaches to obtain ultrasound images from ultrasound raw data. With the emergence of Deep Learning however data driven approaches become feasible and can be explored. These can be used to tak
Autor:
Klaus Eickel, Hannah Strohm, Sven Rothlubbers, Vincent Kuhlen, Jürgen Jenne, Matthias Günther, David Sinden
Publikováno v:
2020 IEEE International Ultrasonics Symposium (IUS).
The emergence of data driven approaches such as Deep Learning has led to novel application of various aspects of science and engineering. It has recently entered the field of ultrasound image beamforming. In this work we investigate neural networks t
Publikováno v:
EMBC
For wireless capsule endoscopy, high quality images need to be transmitted from inside the digestive tract to an on-body receiver. Ultra wideband transmission offers the possibility to achieve much larger data rates than achievable with today’s tec
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery
Purpose We investigate the feasibility of reconstructing ultrasound images directly from raw channel data using a deep learning network. Starting from the raw data, we present the network the full measurement information, allowing for a more generic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a008b41d6a38d66ba6ecbf52b96a0c2
https://publica.fraunhofer.de/handle/publica/263470
https://publica.fraunhofer.de/handle/publica/263470
Publikováno v:
PLoS ONE, Vol 19, Iss 1, p e0295715 (2024)
Racial discrimination adversely impacts health and well-being, and interferes with organizational functioning, including United Nations offices where limited systematic research exists. This article presents and discusses a secondary analysis of data
Externí odkaz:
https://doaj.org/article/81f5930bb36d4329b288ae5c685d7131
Publikováno v:
Intervention Journal of Mental Health and Psychosocial Support in Conflict Affected Areas, Vol 17, Iss 1, Pp 40-49 (2019)
Humanitarian workers experience high symptom burdens of common mental health problems. This requires action from the organisations they are employed with. However, many studies have documented continuing weaknesses in organisational staff support, as
Externí odkaz:
https://doaj.org/article/b8cb8145e3814372bece4b762fb05ae9