在這篇論文中，我們根據量測影像銳利度及雜訊度提出了一個不需參考影像的醫療影像品質評估系統。基於人類視覺系統(HVS)的概念，此一醫療影像品質評估系統設計為區塊模式，並且考慮最小可注意差異模型(JND)，評估的醫療影像品質會透過對比權重以及背景亮度權重加以調整，以達到更符合人類對於醫療影像品質知覺表現的目標。
我們所提出的無參照影像之醫療影像品質評估系統可以獨立運作，不需使用者輸入感興趣區(ROI)；亦可透過使用者輸入的感興趣區而更精確的評估醫療影像品質。感興趣區是醫療人員在使用醫療影像時最關注的部份，用來標示診斷所需要的部份，在影像中使用額外的指引線作為標記。我們所提出的系統也可以支援除了單張影像之外的其他醫療影像種類；例如透過分析指引線(guide wire)的相似度以評估連續型醫療影像的品質。支援這些額外提供的資訊使得我們所提出的無參照影像之醫療影像品質評估系統能夠更有彈性且更符合實務上醫療診斷的需求。
此一系統通過主觀品質評估的檢驗，經由計算與平均評定得分(MOS)的相關度，我們所提出的無參照影像之醫療影像品質評估系統無論在品質評估成果以及預測人類品質知覺表現的能力上，都有不錯的效能。

In this thesis, we propose a no-reference medical image quality assessment system which measures sharpness and noise to be the image quality index. Based on the ideas of human visual system, the image quality assessment metric is block-based and the JND model, such as contrast weighting and background weighting, is introduced into our proposed quality measures to make the results closer to human perceptual performance.
The proposed image quality assessment can work with or without the region of interest information provided by human assessors, which is the most critical region in an image for diagnosis. The proposed medical image quality assessment also has the ability to handle medical image sequences by measuring the gradient correlation on matched guide wire edge blocks. Using this additional information makes our proposed image quality assessment more flexible and practical for diagnostic purpose.
The proposed no-reference medical image quality measure is tested by subjective evaluation. By calculating the correlation with MOS, it shows that our proposed method yields good performance and ability to predict the human perceptual medical image quality.

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