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Št. zadetkov: 2
Prediction of intracranial aneurysm rupture from computed tomography angiography using an automated artificial intelligence framework
June Ho Choi, Jannik Sobisch, Minwoo Kim, Jung Cheol Park, Jae Sung Ahn, Byung Duk Kwun, Žiga Špiclin, Žiga Bizjak, Wonhyoung Park
Izvirni znanstveni članek
Oznake: intrakranialna anevrizma;možganska kap;ruptura;globoko učenje;strojno učenje;intracranial aneurysm;subarachnoid hemorrhage;rupture;machine learning;deep learning;
Intracranial aneurysms (IAs) are common vascular pathologies with a risk of fatal rupture. Human assessment of rupture risk is error prone, and treatment decision for unruptured IAs often rely on expert opinion and institutional policy. Therefore, we aimed to develop a computer-assisted aneurysm rup ...
Leto: 2025 Vir: Fakulteta za elektrotehniko (UL FE)
Assessing accuracy and consistency in intracranial aneurysm sizing
Andrej Planinc, Nina Špegel, Zala Podobnik, Uroš Šinigoj, Petra Skubic, June Ho Choi, Wonhyoung Park, Tina Robič, Nika Tabor, Leon Jarabek, Žiga Špiclin, Žiga Bizjak
Izvirni znanstveni članek
Oznake: variabilnost ocenjevalcev;globoko učenje;intrakranialne anevrizme;intrarater variability;interrater variability;deep learning;intracranial aneurysms;
Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of rupture, which is often fatal. Aneurysm growth of more than 1 mm is considered a surrogate of rupture risk, therefore, this study presents a comprehensive analysis of intracranial aneurysm measurements uti ...
Leto: 2024 Vir: Fakulteta za elektrotehniko (UL FE)
Št. zadetkov: 2
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