Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ecem Sogancioglu"'
Autor:
Ecem Sogancioglu, Keelin Murphy, Erdi Calli, Ernst T. Scholten, Steven Schalekamp, Bram Van Ginneken
Publikováno v:
IEEE Access, Vol 8, Pp 94631-94642 (2020)
In this study, we investigate the detection of cardiomegaly on frontal chest radiographs through two alternative deep-learning approaches - via anatomical segmentation and via image-level classification. We used the publicly available ChestX-ray14 da
Externí odkaz:
https://doaj.org/article/9fad30d8aeb74cd287d5c0af5fdc70ce
Publikováno v:
IEEE Transactions on Medical Imaging, 42, 971-981
IEEE Transactions on Medical Imaging, 42, 4, pp. 971-981
IEEE Transactions on Medical Imaging, 42, 4, pp. 971-981
An important limitation of state-of-the-art deep learning networks is that they do not recognize when their input is dissimilar to the data on which they were trained and proceed to produce outputs that will be unreliable or nonsensical. In this work
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b8a4c232cfb5c8a614ed69a9fce6480
https://pubmed.ncbi.nlm.nih.gov/36374875
https://pubmed.ncbi.nlm.nih.gov/36374875
Autor:
Erdi Calli, Bram van Ginneken, Keelin Murphy, Ernst T. Scholten, Steven Schalekamp, Ecem Sogancioglu
Publikováno v:
IEEE Access, Vol 8, Pp 94631-94642 (2020)
IEEE Access, 8, 94631-94642
IEEE Access, 8, pp. 94631-94642
IEEE Access, 8, 94631-94642
IEEE Access, 8, pp. 94631-94642
In this study, we investigate the detection of cardiomegaly on frontal chest radiographs through two alternative deep-learning approaches - via anatomical segmentation and via image-level classification. We used the publicly available ChestX-ray14 da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e48cdafaaa8959b2f017925e6b2b08b1
https://doi.org/10.1109/access.2020.2995567
https://doi.org/10.1109/access.2020.2995567
Autor:
Julia M. H. Noothout, Nikolas Lessmann, Matthijs C. van Eede, Louis D. van Harten, Ecem Sogancioglu, Friso G. Heslinga, Mitko Veta, Bram van Ginneken, Ivana Išgum
Publikováno v:
Journal of Medical Imaging, 9
Journal of medical imaging (Bellingham, Wash.), 9(5):052407. SPIE
Journal of Medical Imaging, 9, 5
Journal of medical imaging (Bellingham, Wash.), 9(5):052407. SPIE
Journal of Medical Imaging, 9, 5
Contains fulltext : 252007.pdf (Publisher’s version ) (Open Access) Purpose: Ensembles of convolutional neural networks (CNNs) often outperform a single CNN in medical image segmentation tasks, but inference is computationally more expensive and ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15eefd6de502d73504e5b1b940aca01a
http://hdl.handle.net/2066/252007
http://hdl.handle.net/2066/252007
Publikováno v:
IEEE Transactions on Control Systems Technology, 29, 1891-1906
IEEE Transactions on Control Systems Technology, 29(5)
IEEE Transactions on Control Systems Technology, 29, 5, pp. 1891-1906
IEEE Transactions on Control Systems Technology, 29(5)
IEEE Transactions on Control Systems Technology, 29, 5, pp. 1891-1906
Seasonal thermal energy storage systems (STESSs) can shift the delivery of renewable energy sources and mitigate their uncertainty problems. However, to maximize the operational profit of STESSs and ensure their long-term profitability, control strat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca019b51d1a060a1348b14f1f10c3cf5
http://resolver.tudelft.nl/uuid:03a5aabc-d61f-4e25-b20c-4a7a56780ebc
http://resolver.tudelft.nl/uuid:03a5aabc-d61f-4e25-b20c-4a7a56780ebc
Publikováno v:
Medical Image Analysis, 72
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a particularly important modality for which a variety of applications h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb36346b12b6685bb8a3640e0df63bc0
Publikováno v:
Medical Imaging: Computer-Aided Diagnosis
In this work we analyze the effect of label noise in training and test data when performing classification experiments on chest radiographs (CXRs) with modern deep learning architectures. We use ChestXRay14, the largest publicly available CXR dataset
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49b3cdaa129eea75519e0c9d977c6a68
https://doi.org/10.1117/12.2514290
https://doi.org/10.1117/12.2514290
Building day-ahead bidding functions for seasonal storage systems: A reinforcement learning approach
Publikováno v:
IFAC-Papers
IFAC-PapersOnLine, 52(4)
IFAC-PapersOnLine, 52(4)
Due to the increasing integration of renewable sources in the electrical grid, electricity generation is expected to become more uncertain. In this context, seasonal thermal energy storage systems (STESSs) are key to shift the delivery of renewable e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a55b8746f4f4ffb6e8d8cdcf5c6f4bc