Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Salari, Soorena"'
Early surgical treatment of brain tumors is crucial in reducing patient mortality rates. However, brain tissue deformation (called brain shift) occurs during the surgery, rendering pre-operative images invalid. As a cost-effective and portable tool,
Externí odkaz:
http://arxiv.org/abs/2308.10784
Accurate identification and quantification of unruptured intracranial aneurysms (UIAs) is crucial for the risk assessment and treatment of this cerebrovascular disorder. Current 2D manual assessment on 3D magnetic resonance angiography (MRA) is subop
Externí odkaz:
http://arxiv.org/abs/2308.03001
Homologous anatomical landmarks between medical scans are instrumental in quantitative assessment of image registration quality in various clinical applications, such as MRI-ultrasound registration for tissue shift correction in ultrasound-guided bra
Externí odkaz:
http://arxiv.org/abs/2307.14523
In brain tumor resection, accurate removal of cancerous tissues while preserving eloquent regions is crucial to the safety and outcomes of the treatment. However, intra-operative tissue deformation (called brain shift) can move the surgical target an
Externí odkaz:
http://arxiv.org/abs/2307.14520
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2023)
Intracranial hemorrhage (ICH) is a life-threatening medical emergency that requires timely and accurate diagnosis for effective treatment and improved patient survival rates. While deep learning techniques have emerged as the leading approach for med
Externí odkaz:
http://arxiv.org/abs/2304.04902
Autor:
Abdar, Moloud, Salari, Soorena, Qahremani, Sina, Lam, Hak-Keung, Karray, Fakhri, Hussain, Sadiq, Khosravi, Abbas, Acharya, U. Rajendra, Makarenkov, Vladimir, Nahavandi, Saeid
Publikováno v:
Information Fusion 2023
The COVID-19 (Coronavirus disease 2019) pandemic has become a major global threat to human health and well-being. Thus, the development of computer-aided detection (CAD) systems that are capable to accurately distinguish COVID-19 from other diseases
Externí odkaz:
http://arxiv.org/abs/2105.08590
Autor:
Salari, Soorena, Sadati, Nasser
This paper presents a novel feature fusion-based deep learning model (called CASU2Net) for fault detection in offshore wind turbines. The proposed CASU2Net model benefits of a two-step early fusion to enrich features in the final stage. Moreover, sin
Externí odkaz:
http://arxiv.org/abs/2011.12130
Autor:
Abdar, Moloud, Salari, Soorena, Qahremani, Sina, Lam, Hak-Keung, Karray, Fakhri, Hussain, Sadiq, Khosravi, Abbas, Acharya, U. Rajendra, Makarenkov, Vladimir, Nahavandi, Saeid
Publikováno v:
In Information Fusion February 2023 90:364-381
Akademický článek
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Publikováno v:
International Journal of Computer Assisted Radiology & Surgery; Mar2023, Vol. 18 Issue 3, p501-508, 8p