Zobrazeno 1 - 10
of 190
pro vyhledávání: '"Irene Yu-Hua Gu"'
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
BackgroundDeep learning (DL) has shown promising results in molecular-based classification of glioma subtypes from MR images. DL requires a large number of training data for achieving good generalization performance. Since brain tumor datasets are us
Externí odkaz:
https://doaj.org/article/9bb8f571f2f9481685527eff231ce67c
Autor:
Muhaddisa Barat Ali, Irene Yu-Hua Gu, Alice Lidemar, Mitchel S. Berger, Georg Widhalm, Asgeir Store Jakola
Publikováno v:
BMC Biomedical Engineering, Vol 4, Iss 1, Pp 1-11 (2022)
Abstract Background For brain tumors, identifying the molecular subtypes from magnetic resonance imaging (MRI) is desirable, but remains a challenging task. Recent machine learning and deep learning (DL) approaches may help the classification/predict
Externí odkaz:
https://doaj.org/article/0beec643838b46c78f9d689e79476289
Publikováno v:
BMC Medical Imaging, Vol 20, Iss 1, Pp 1-11 (2020)
Abstract Background This paper addresses issues of brain tumor, glioma, classification from four modalities of Magnetic Resonance Image (MRI) scans (i.e., T1 weighted MRI, T1 weighted MRI with contrast-enhanced, T2 weighted MRI and FLAIR). Currently,
Externí odkaz:
https://doaj.org/article/84369f4028ec476fa5e54dc9190f78a3
Publikováno v:
IEEE Access, Vol 8, Pp 22560-22570 (2020)
This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available gl
Externí odkaz:
https://doaj.org/article/a7156a80fc2048799907cd0f5d58f0fd
Publikováno v:
Sensors, Vol 22, Iss 14, p 5292 (2022)
In most deep learning-based brain tumor segmentation methods, training the deep network requires annotated tumor areas. However, accurate tumor annotation puts high demands on medical personnel. The aim of this study is to train a deep network for se
Externí odkaz:
https://doaj.org/article/d702eb1476124b4a9ec0ac43335eade6
Autor:
Yixiao Yun, Irene Yu-Hua Gu
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2017, Iss 1, Pp 1-13 (2017)
Abstract In this paper, we address the problem of classifying activities of daily living (ADL) in video. The basic idea of the proposed method is to treat each human activity in the video as a temporal sequence of points on a Riemannian manifold and
Externí odkaz:
https://doaj.org/article/a7098220d60347c491d46b9c83d6484a
Publikováno v:
Applied Sciences, Vol 11, Iss 8, p 3598 (2021)
Power quality (PQ) is an increasing concern in the distribution networks of modern industrialized countries. The PQ monitoring activities of distribution system operators (DSO), and consequently the amount of PQ measurement data, continuously increas
Externí odkaz:
https://doaj.org/article/ccfc4acc6aa7402bac4732e90b05842b
Autor:
Muhaddisa Barat Ali, Irene Yu-Hua Gu, Mitchel S. Berger, Johan Pallud, Derek Southwell, Georg Widhalm, Alexandre Roux, Tomás Gomez Vecchio, Asgeir Store Jakola
Publikováno v:
Brain Sciences, Vol 10, Iss 7, p 463 (2020)
Brain tumors, such as low grade gliomas (LGG), are molecularly classified which require the surgical collection of tissue samples. The pre-surgical or non-operative identification of LGG molecular type could improve patient counseling and treatment d
Externí odkaz:
https://doaj.org/article/4638892229b847779163ca2ade06dd6b
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 70:1-10
This article proposes a novel scheme for analyzing power system measurement data. The main question that we seek answers in this study is on “whether one can find some important patterns that are hidden in the large data of power system measurement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c28b9f2ddd4f75ce76615763065de89f
https://doi.org/10.1109/tim.2020.3016408
https://doi.org/10.1109/tim.2020.3016408
Publikováno v:
BMC Medical Imaging, Vol 20, Iss 1, Pp 1-11 (2020)
BMC Medical Imaging
BMC Medical Imaging
Background This paper addresses issues of brain tumor, glioma, classification from four modalities of Magnetic Resonance Image (MRI) scans (i.e., T1 weighted MRI, T1 weighted MRI with contrast-enhanced, T2 weighted MRI and FLAIR). Currently, many ava
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::855e96bf62e77ed9567cbefa04d4a17c
http://link.springer.com/article/10.1186/s12880-020-00485-0
http://link.springer.com/article/10.1186/s12880-020-00485-0