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標題: 影像正規化對腕骨切割之評估
An Estimation on the Carpal Bone Extraction Using Intensity Normalization
作者: Ting-Jyun Peng
關鍵字: z transform
Bone Age
Image Segmentation
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摘要: Assessing bone age by viewing hand radiographs plays a critical role in clinical pediatric endocrinology. According to the past researches, to assess bone ages by phalanx features among 0 to 7 years old may get the worse bone age assessment accuracy as the smaller ages goes. The clinical researches had indicated that among the ages from newborn to about 7 years old, the maturation of carpal bones appear in a specific order and separate from each other. And the features among the period that the carpal bones begin fusing in about 8 years old has been proven effective in a research of recent years. For these reasons, to assess bone age had demonstrated to be reliable under this range of ages. However, the process of extracting the carpal region of interest (CROI) from radiographs is usually coupled with such image quality problems like low contrast, non-uniformly or over-low exposure. Hence it is quite challengeable task to separate the pixels represent the bone tissue from the soft tissue in radiographs. This dissertation proposed an image intensity normalization method which applied the transform function, z transform in Statistics. By transforming each intensity value found in an image to z value respectively, all the radiographs from heterogeneous sources can be normalized into one consistent standard. The pixels represent the carpal bones in radiographs are segmented by intensity thresholding. With respect to balanced accuracy, the chosen criteria of segmentation accuracy in this dissertation, the experiment results reveal proposed method raises the performance of control group obviously and outperforms the image intensity normalization methods including linear normalization, histogram equalization and contrast limited histogram equalization, which are often used in medical image processing. In addition, the average balance accuracy of the samples normalized by proposed method and grouped by rounded bone age all reach about 80 percent.
從手掌X光影像估測骨齡,在兒童內分泌的問題及成長失調的診斷上扮演著極重要的角色。文獻顯示在骨齡估測方法的研究上,若是依靠指骨特徵對0~7歲的幼童估測骨齡得出的效果不佳,而且年齡愈小這種現象愈明顯。而在醫學上的研究顯示,從新生兒到7歲左右的兒童,每一塊腕骨的成長是依序出現且相互分離,並且在8歲腕骨開始癒合時的特徵也在近幾年的研究中得到有效的證實。因此在這一個階段利用腕骨做幼童的骨齡估測被認為是可信賴的。但是在萃取腕骨感興趣區域(CROI)的過程中,常遭遇到X光影像低對比、照度不均或是曝光過多或不足的問題。因此,要能夠從手掌X光影像中,將顯示骨骼的像素從軟組織中分離出來,是相當具有挑戰性的工作。本論文應用統計學上的z轉換,提出一個影像亮度正規化的方法,首先將影像中的各灰階值轉換成相對應的z值,讓各種來源不同的X光影像亮度可以校正到一致的標準,之後再選取適當的門檻值來切割腕骨影像。實驗結果顯示,本方法在balanced accuracy上相較於對照組能夠明顯的提高切割正確率,與過去研究醫學影像上常用的亮度正規化方法包括線性正規化、直方圖等化、CLAHE等演算法相比,有更佳的樣本平均切割正確率,另外對於1~ 8歲骨齡樣本各自分群的平均正確率可達80%左右。
其他識別: U0005-2606201414272500
文章公開時間: 2016-12-16
Appears in Collections:資訊科學與工程學系所



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