使用人工智慧於醫療影像的分析

科技時代的來臨，逐漸地改變人們的生活型態。現今有許多人工智慧的產品深入所有人的生活之中。將人工智慧應用於金融行業已相對成熟，而對於醫療產業仍逐年冉冉上升，其中醫學影像是非常熱門與重要的一環，可以透過大量的醫學影像與數據資料去分析不同種疾病並將其分類，也可以協助醫師快速辨別身體部位有無癌症與病變，減輕醫師的負擔並減少其誤判。因此本研究使用Github上的開源資料作為來源，並與中部某醫院的醫師進行合作。本研究主要辨別腦小血管疾病(CSVD)，並使用腦部MRI T1 FLAIR與 MRI T2 FLAIR的醫學影像，作為是否有罹患CSVD的醫學影像資料，再進行資料讀取與特徵點擷取，最後將這些資料放入模型之中訓練。藉由此影像辨識系統可讓醫師做為參考，降低醫師大量判讀醫學影像時的負擔並快速判讀，來提高醫師看診效率。

關鍵字

人工智慧；影像辨識；醫學影像；機器學習

並列摘要

The advanced modern technology nowadays has changed people life style. There are many artificial intelligence (AI) products imbed in our daily life. The AI industry not only helps the financial business but also the medical treatment improvement. The image analysis used to play an important role in medical field, and it is now easier to implement the image analysis due to the mature of AI technology. One can apply numerous medical images to analyze and categories disease with machine learning approach. This has helped the physicians to identify the type and the location of disease and provide speedy cure for the patients. This research utilizes the AI approaches available on Github and works with the hospital in central south for the detection of Cerebral Small Vessel Disease (CSVD). The AI program mainly uses the MRI T1 FLAIR and T2 FLAIR images to decide whether it is CSVD images. With this research, the physicians can detect CSVD efficiently and the load of reading MRI images has dramatically reduced.

並列關鍵字

Artificial Intelligence ； Images Analysis ； Medical Images ； Machine Learning

參考文獻

[1] 科技部，加速醫療影像AI發展再創台灣優勢科技部啟動台灣首座跨醫療院所之醫療影像標註資料庫，取自https://www.most.gov.tw/folksonomy/detail?article_uid=9eafcc53-50c3-4803-aff6-fa578c25b1f7&menu_id=9aa56881-8df0-4eb6-a5a7-32a2f72826ff&l=ch。

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使用人工智慧於醫療影像的分析

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