⏱️ 10/7 (Thur.) 20:45-21:10 at Online Track 1
Stereotactic radiosurgery (SRS), a validated treatment for brain tumors, requires accurate tumor contouring. This manual segmentation process is time-consuming and prone to substantial inter-practitioner variability.
Artificial intelligence (AI) with deep neural networks have increasingly been proposed for use in lesion detection and segmentation.
We validated AI-assisted contouring in a clinical setting. Less-experienced clinicians gained prominent improvement on contouring accuracy but less benefit in reduction of working hours.
By contrast, SRS specialists had a relatively minor advantage in accuracy, but greater timesaving with the aid of AI.
Deep learning neural networks can be optimally utilized to improve accuracy and efficiency for the clinical workflow in brain tumor SRS.
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EDUCATION AND TRAINING: National Taiwan University College of Medicine Taipei, Taiwan M.D. Medicine 1995 National Taiwan University Hospital Department of Surgery Taipei, Taiwan Residency Neurosurgery 2003 Stanford University Medical CenterStanford, CA, USA Fellowship Stereotactic Radiosurgery 2007. UCLA Medical Center Los Angeles, CA, USA Fellowship. Neurosurgery. 2009. Institute of Biomedical Engineering National Taiwan University MD Ph.D. Biomedical Engineering 2011 POSITIONS: Clinical Assistant Professor, National Taiwan University Hospital, Department of Surgery. Specializing in stereotactic radiosurgery, spine surgery and neurotrauma 2012-Present Neurosurgeon, National Taiwan University HospitalDepartment of Neurosurgery 2005-Present. Neurosurgeon, National Taiwan University Hospital Yunlin Branch. 2004-2005. Neurosurgeon, Yunlin General Hospital Department of Health 2003-2004 RESEARCH INTERESTS: •Stereotactic Radiosurgery •Brain tumor •Spine •Medical image analysis •Clinical data mining
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