臺灣博碩士論文加值系統

根據行政院衛生署中央健康保險局的醫療統計資料顯示，民國一百年外傷患者門、住診人數總計10,644,270 人，國人因骨折就醫人數達 609,959 人，平均不到一分鐘就有國人因骨折而就醫。骨折的種類分為二種，一種為閉合性骨折，另一種為開放性骨折。此二種骨折的形態包括橫向骨折、斜向骨折、螺旋骨折、壓迫性骨折、破裂骨折、粉碎性骨折、龜裂骨折、脫臼骨折等。以病人的主訴(痛、腫、骨破裂音及變形) 及X 光片做為診斷。骨折的個案中，因外力所造成的骨折，在第一次X 光片檢查後無法正確判斷解讀而造成誤判的情形下，未選擇正確的治療，將導致後來的癒合不良、肌肉萎縮、關節僵硬、長短腳等手術的後遺症，其結果為重複開刀治療，不僅費時、費力，更浪費醫療資源。因此本論文使用直方圖加強，針對疑似骨折的部位轉正、翻轉、裁切正規化擷取與正常的骨頭相對應部位；正常骨頭與疑似骨折正規化後以高斯平滑雜訊；Sobel 濾波運算元做邊緣的檢測、擷取邊緣；以正常骨頭圖像做Morphing 的變形影像處理；再將正常骨頭變形後做亮度均衡與骨折部位正規化亮度平均；接著骨折部位正規化與正常骨頭變形兩張圖像做相減處理；最後運用Threshold 使圖像二值化強化邊緣，以突出異變圖像位置提供重要的資訊予以醫師觀察有無骨折病徵發生。本研究期以未來能輔助醫師在骨折X 光片正確快速的判讀，讓骨折的個案接受最正確與適當的手術治療。

According to medical statistics , Department of Health National Health Insurance Bureau, Republic of China a century door trauma patients , a total of 10,644,270 people live in the number of clinics , doctor fracture due to the number of people who reached 609,959 , an average of less than a minute because there are people fractures doctor. Types of fractures are divided into two kinds , one for closed fracture , the other for open fractures . This includes two transverse fracture morphology of fracture , oblique fracture , spiral fracture, compression fracture , rupture fracture, fracture, crack fracture, dislocation fractures. To the patient's chief complaint ( pain, swelling, bone fracture and deformation sound ), and X-rays as a diagnostic . Cases of fracture , because fracture caused by external forces , after the first X-ray examination can not correctly interpret and judge the case caused a miscarriage of justice , do not select the right treatment , and later will lead to poor healing , muscle atrophy, joint stiffness , the length of the foot , such as the aftermath of surgery , the result of repeated surgical treatment , not only time-consuming , laborious, and more waste of medical resources. Therefore we use the histogram to strengthen against the suspected fracture site to positive , flip , crop, capture and formalize the corresponding parts of the normal bone ; normal bone and suspected fractures after normalization with Gaussian smoothing noise ; Sobel filter operands do edge detection , capture edges ; do Morphing normal bone image distortion image processing ; then do the normal bone deformation and fracture site normalization balanced brightness brightness average ; followed by normalization with normal bone fracture site deformed two images do subtraction processing ; Finally, we use a threshold to strengthen the image binary edge image to highlight the position of the mutation to provide important information to be physicians to observe whether the fracture symptoms occur. The study period in the future could help physicians quickly correct interpretation of the fracture X-rays , so that most cases of fracture of the right to accept and appropriate surgical treatment.

摘要 ………………………………………………………...………………..……i
Abstract ……………………………………………………………..…………..……ii
目錄 ………………………………………………………………………..…… iii
圖目錄 …………………………………………………………………….…..……v
表目錄 ………………………………………………………………………..…viii
第一章導論 …………………………………………………………………..……1
1.1 研究背景 ………………………………………………………………………..1
1.2 研究目的 ………………………………………………………………………..2
1.3 論文架構 ………………………………………………………………………..2
第二章影像處理文獻探討 ………………………………………………………..3
2.1 X-ray ………………………………………………………………………..……4
2.2 數位影像處理影像增強(Enhancement) ………………………………………..5
2.2.1 對比度增強 ………………………………………………………..……5
2.2.2 直方圖增強 …………………………………………………………..…6
2.2.3 數字圖像的算術運算 …………………………………………………..8
2.3 空間域濾波增強 ……………………………………………………………..8
2.3.1 影像的平滑增強處理 …………………………………………………10
2.3.1.1 平滑線性空間濾波器 ………..……………………………..……11
2.3.1.2 平滑非線性空間濾波器 …………………..…………………..……14
2.3.2 邊緣增強 …………………………………………..………………..……16
2.3.3 Threshold ……………………………………………………..……..……20
2.4 國內圖像比對相關研究 ………………………………………………………22
2.4.1 小結 ………………………………………………………………………23
2.5 Morphing 變形 …………………………………………………………………24
2.5.1 Morphing 變形變換方式 …………………………………………………26
2.5.2 貝爾尼利的運算方式 ……………………………………..……..……26
2.5.3 特徵線 ……………………………………………………..……..……27
2.5.4 映射 …………………………………………………………..……..……30
第三章架構設計與影像處理研究 ……………………………………………35
3.1 系統架構設計………………………………………………………………….35
3.2 影像來源、軟體、硬體規格 ……..……………………………………..……35
3.3 影像處理研究 …………………………………………………..………..……36
3.3.1 直方圖增強 ……………………………………………………………37
3.3.2 數位圖像的算術運算 ……………………………………..……..……40
iv
3.3.3 影像的平滑增強處理 ……………………………………………..……41
3.3.3.1 平滑線性空間濾波器鄰域平均法 ……………………………..……42
3.3.3.2 高斯濾波 ……………………………………………….……..……43
3.3.3.3 中值濾波 ………………………………………………….…..……45
3.3.3.4 最大值濾波 ………………………………………….……..……46
3.3.3.5 最小值濾波 ……………………………………….………..……47
3.3.3.6 Soften 柔和…………………………………………………..………….48
3.3.3.7 模糊Blu …………………………………………….………..……49
3.3.3.8 抗鋸齒濾波Anti Alias ……………………………………...……50
3.3.4 邊緣增強Edge Enhanced ………………………………………………...50
3.3.4.1 線性檢測Lines ……………………………………………………...55
3.3.4.2 Sobel 邊緣檢測和邊緣細化 …………………………………...…56
3.3.4.3 普魯伊特Prewitt 運算元 ………………………………………...…58
3.3.4.4 羅賓遜Robinson 運算元 …………………………………...………60
3.3.4.5 基爾希Kirsch 邊緣檢測 ……………………………………...……61
3.3.4.6 Roberts 運算元 ……………………………………….………..……62
3.3.4.7 位移及相位邊緣強化 ………………………….…………..……63
3.3.5 浮雕emboss 濾波 …….…………………………………………..……63
3.3.5.1 雕塑sculpture 濾波 ……….…………………………………..……65
3.3.5.2 光刻濾波Lithography ….…………………………………..……65
3.3.6 拉普拉斯濾波 …….………………………………………………..……66
3.3.6.1 高斯-拉普拉斯Laplacian of Gaussian …….………………..……68
3.3.7 Threshold ….………………………………………………………..……68
3.4 X 光攝影醫學影像正規化 …………………………….……………..……71
3.4.1 裁切 ………………………………………………….……………..……71
3.4.2 旋轉Rotate ……………………………………………….……..……72
3.4.3 左右翻轉 ………………………………….………………………..……73
3.5 Morphing 比對………………………………….………………………..……74
3.5.1 外型描繪 …………………………………….……………………..……74
3.5.2 圖像映射 ………………………………………….………………..……79
3.5.3 像素插值 …………………………………………….……………..……85
第四章影像處理結果………………………………………..……………..……90
4.1 檢視比對研究結果 ………………………………………….…………..……90
4.2 影像處理實驗結果 ……………………………………….……………..……91
第五章結論與建議 ………………………………………….…………..……97
參考文獻 …………………………………………….…………………..……98

[1]陳偉銘、趙涵捷“中山文庫 影像裡的數學世界” 2001 初版
[2]Gonzalez, Woods 原著 繆紹綱譯 “數位元影像處理” 2009 初版一刷
[3]鍾國亮“ 影像處理與電腦視覺”2008 四版
[4]賴岱佑, 劉敏著“數位元影像處理技術手冊” 2007
[5]田捷 “醫學影像處理與分析”2003
[6] 'WIKIPEDIA'The Free Encyclopedia ,http://en.wikipedia.org/wi ki/Main_Page,
[7] '百度百科'全球最大中文百科全书, http://baike.baidu.com/
[8] 'A+醫學百科'在線醫學百科全書網站,http://cht.a-hospital.com/w/
[9] Araujo、Davis Jr、Daker、Souza、Brazil “Digital Processing Of X-rays Of Sculptures: A Case Study Of Aleijadinhos Work”
[10] Srikanth Rangarajan“Algorithms For Edge Detection”
[11] Dileepan Joseph “Edge enhancement by linear (and nonlinear)
[12] filtering”University of Oxford,UK-Dept.of Engineering Science ,Dr
[13] Yao Wang“Image Filtering: Noise Removal,Sharpening,Deblurring” 2006
[14] Thaddeus Beier“Feature-Based Image Metamorphosis”，Silicon Graphics Computer，Systems 2011 Shoreline Blvd,
[15] Иаиа Аиа“Морфинг – преобразование изображений”，дипломная работа，2010
[16] Evan Wallace“CS 195-G: Face Morphing”
[17] Swarup Deepika Jagmohan“Computer Graphics”2002
[18] Beier and Neely’s Morphing Method“Image Warping and Morphing ”
[19] Henry Johant“Morphing Using Curves and Shape Interpolation Techniques”2000
[20] Siti Arpah Bt Ahmadi“,The Effect of Sharp Contrast-Limited Adaptive Histogram Equalization (SCLAHE)on Intra-oral Dental Radiograph Images”2010
[21] S.Sathish Kumarl, “Edge Detection of Angiogram Images Using the Classical Image Processing Techniques”2012
[22] Song Tie-Rui “The Research of X-ray Bone Fracture Image Enhancement Algorithms”2010
[23] Zheng Wei, Yang Hua “X-ray Image Enhancement Based on Multiscale Morphology”2007
[24] Foisal Hossain “Medical Image Enhancement Based on Nonlinear Technique and Logarithmic Transform Coefficient Histogram Matching”2010
[25] 蔣秉珊“以顏色、紋理、形狀特徵為基礎之觀賞魚影像檢索系統”,宜蘭大學,資訊工程研究所碩士論文2011