Technical Name Auto Segmentation App. for Predication of Arteriovenous Malformation
Project Operator Taipei Medical University
Project Host 彭徐鈞
Summary
By automatic clustering and fuzzy classification algorithm technology, we develop an "ASAP-brain radiotherapy risk assessment software", which can evaluate the treatment risk of patients with brain diseases immediately through MRI images, leading to reduce the probability of prognosis complications. The medical software of ASAP-AVM is co-developed by Taipei Medical University (TMU) and Taipei Veterans General Hospital (TVGH) to evaluate the radiotherapy risk for patients with arteriovenous malformation (AVM). ASAP-AVM can automatically detect the site of vascular malformation in the brain tissue in a MRI image and calculate the actual content between normal brain tissue and AVM, respectively. For the neurological surgeons and radiologists, ASAP-AVM can provide personalized and accurate radiotherapy evaluation for AVM patients in real time, which can effectively reduce the brain damage and the incidence of complications including cerebral edema and epilepsy.
Scientific Breakthrough
The medical software of ASAP-AVM is co-developed by Taipei Medical University (TMU) and Taipei Veterans General Hospital (TVGH) to evaluate the radiotherapy risk for patients with arteriovenous malformation (AVM). ASAP-AVM can automatically detect the site of vascular malformation in the brain tissue in a MRI image and calculate the actual content between normal brain tissue and AVM, respectively. For the neurological surgeons and radiologists, ASAP-AVM can provide personalized and accurate radiotherapy evaluation for AVM patients in real time, which can effectively reduce the brain damage and the incidence of complications including cerebral edema and epilepsy.
Industrial Applicability
Medical imaging accounts for 80% of medical information, and the judgment results of physicians on imaging may also vary according to experience. The introduction of ASAP-AVM application analysis can provide reference basis when doctors have difficulty in evaluation, can improve medical efficiency and reduce the risk after radiation treatment. By combining Taiwan's computing and data processing capabilities with strong clinical resources, it will play a role in this AI and machine learning innovation project, and will lead to progress in related AI-med tech industries. We can develop treatment risk analysis modules with international radiotherapy equipment manufacturers including GE Healthcare (USA), Siemens Healthcare (USA), Toshiba Healthcare (Japan), Elekta (Sweden), etc.
Keyword Cerebral Arterio-Venous Malformation Gamma knife radiosurgery Radiotherapy Stereotactic radiosurgery Leksell Gamma Plan Precision medicine Image analysis Unsupervised classification Fuzzy c-means clustering Software as a medical device
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