Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Anne Jian"'
Autor:
Karol Wiśniewski, Piotr Reorowicz, Zbigniew Tyfa, Benjamin Price, Anne Jian, Andreas Fahlström, Damian Obidowski, Dariusz J. Jaskólski, Krzysztof Jóźwik, Katharine Drummond, Lars Wessels, Peter Vajkoczy, Alexios A. Adamides
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Unruptured giant intracranial aneurysms (GIA) are those with diameters of 25 mm or greater. As aneurysm size is correlated with rupture risk, GIA natural history is poor. Parent artery occlusion or trapping plus bypass revascularization shou
Externí odkaz:
https://doaj.org/article/ebf03e4dc2834af5996a9f74f2b6233a
Publikováno v:
Neurosurgery. 91:8-26
Survival prediction of patients affected by brain tumors provides essential information to guide surgical planning, adjuvant treatment selection, and patient counseling. Current reliance on clinical factors, such as Karnofsky Performance Status Scale
Publikováno v:
Neuroradiology. 64:647-668
Purpose To systematically review the literature regarding the application of machine learning (ML) of magnetic resonance imaging (MRI) radiomics in common sellar tumors. To identify future directions for application of ML in sellar tumor MRI. Methods
Publikováno v:
Neuroradiology. 63:1253-1262
Accurate brain tumor segmentation on magnetic resonance imaging (MRI) has wide-ranging applications such as radiosurgery planning. Advances in artificial intelligence, especially deep learning (DL), allow development of automatic segmentation that ov
Publikováno v:
Acta neurochirurgica. Supplement. 134
The heterogeneity of brain tumours at the molecular, metabolic and structural levels poses significant challenge for accurate tissue characterisation. Artificial intelligence and radiomics have emerged as valuable tools to analyse quantitative featur
Publikováno v:
Acta Neurochirurgica Supplement ISBN: 9783030852917
The heterogeneity of brain tumours at the molecular, metabolic and structural levels poses significant challenge for accurate tissue characterisation. Artificial intelligence and radiomics have emerged as valuable tools to analyse quantitative featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b764e5f362f965a6d6e81a660a3beb1
https://doi.org/10.1007/978-3-030-85292-4_22
https://doi.org/10.1007/978-3-030-85292-4_22
Publikováno v:
Neuroradiology. 64(4)
To systematically review the literature regarding the application of machine learning (ML) of magnetic resonance imaging (MRI) radiomics in common sellar tumors. To identify future directions for application of ML in sellar tumor MRI.PubMed, Medline,
Autor:
Antonio, Di Ieva, Carlo, Russo, Sidong, Liu, Anne, Jian, Michael Y, Bai, Yi, Qian, John S, Magnussen
Publikováno v:
Neuroradiology. 63(8)
Accurate brain tumor segmentation on magnetic resonance imaging (MRI) has wide-ranging applications such as radiosurgery planning. Advances in artificial intelligence, especially deep learning (DL), allow development of automatic segmentation that ov
Publikováno v:
Neurosurgery. 89(1)
Background Molecular characterization of glioma has implications for prognosis, treatment planning, and prediction of treatment response. Current histopathology is limited by intratumoral heterogeneity and variability in detection methods. Advances i
Autor:
Julie R. McMullen, My-Nhan Nguyen, Xiao-Jun Du, Xiao-Ming Gao, Anne Jian, Helen Kiriazis, Yidan Su, Diego Ruggiero, Li-Ping Han
Publikováno v:
American Journal of Physiology-Heart and Circulatory Physiology. 309:H946-H957
Myocardial fibrosis is regarded as a pivotal proarrhythmic substrate, but there have been no comprehensive studies showing a correlation between the severity of fibrosis and ventricular tachyarrhythmias (VTAs). Our purpose was to document this relati