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電腦自動化程式預測兒童矯正患者骨骼生長之研究

Prediction of Bone Age Using Computerized System in Children

摘要


研究目的:本研究之目的為設計電腦輔助系統程式以輔助牙醫師做出正確骨骼生長情形之診斷。此系統並可隨著輸入資料量之增加,而提升骨年齡判斷之準確性。對新進醫師的訓練也可利用此系統資料庫建立訓練系統。研究方法:本研究將開發更準確之手部關節特徵粹取,並且以自動化的方式判定特徵關節的位置以及關節的特徵,藉以獲得更為準確的骨年齡測定。從台中榮總放射線部收集8~18歲青少年之手掌骨X光片,將此手部X光片之影像以電腦來粹取其特徵及生長之情形。利用手部X光影像做骨年齡偵測,首先先對影像作縮減,以加快電腦運算速度,再利用局部二值化法,將手骨粹取出來而去掉肉的部分,之後利用粹取出來的手骨,以細線化的方式得到手指的骨架,再讀出原始影像在骨架上的灰階值,並計算灰階值的變化,藉以偵測出特徵關節的位置。本自動化電腦輔助流程包括下列五個步驟:背景雜訊修消除、手骨影像角度調整、關節位置萃取、骨年齡指數計算及骨年齡之估計。結果與結論:關節中骨年齡判斷主要是以關節中間的骨頭做判斷,為了估計骨年齡,我們利用影像中關節區域計算與骨年齡相關性高的指數作為依據。從手骨影像中可以看出,三個指節中,中指第三指節有較高的相關性。而三個指數中又以最寬寬度及到下邊界距離比有較高的分辨率。綜合來說,是以第二指節配合最寬寬度及到下邊界距離比的誤差最小。結果顯示以單個關節配合單一指數進行估計,第二指節配合最寬寬度及到下邊界距離比的誤差最小。未來此演算法可以利用非線性方程式發展為多關節配合多指數之演算法,如類神經網路及非線性投影。之後將加入更多訓練影像以提升判斷的準確性。

並列摘要


Bone age assessment using a Hand wrist film and cephalometric is an important clinical tool in orthodontics to predict growth potential of children. Details analysis of the appearance and growth of specific bones in a developing child to predict the growth potential of the child is the common assessment method used in orthodontics. This subjective procedure is very time consuming and affected by clinician's experience. Automatically identifying and classifying interesting bones of these radiographs can be made easier if suitable models of the desire stages are available. The purpose of this investigation was to develop an automatically identifying assessment system to determine the growth stage of hand-wrist film.Hand-wrist films were collected from the data base of Taichung Veterans General Hospital. Ten x-rays from each age group were collected from children age between 8-18. Automation process of bone classification and identification were performed in these x-ray films. The automation process included 1. Background removal 2. Orientation correction 3. Detection of phalangeal tips 4. Extraction of epiphyseal/metaphyseal regions of interest and 5. Estimation of the skeletal developmental stages.Develop an automatic identification system for bone maturation stage will be done in the future. And this automatic computerized system will be applied to clinical patients in the future to judge the accuracy of this computerized assessment system.

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