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研究生:吳佳翰
研究生(外文):Chia-Han Wu
論文名稱:結合有損與無損的醫學影像壓縮技術
論文名稱(外文):A Hybrid Distortion/Distortionless Medical Image Compression
指導教授:楊慶隆楊慶隆引用關係
指導教授(外文):Ching-Nung Yang
學位類別:碩士
校院名稱:國立東華大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:47
中文關鍵詞:關鍵性區域影像壓縮非關鍵性區域門檻值法動態關鍵區域偵測
外文關鍵詞:ROIRONILossless CompressionJPEG2000 Compression
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隨著資訊科技的發展,醫學影像擷取技術也不斷進步,使得影像的數位檔案體積越來越大,造成各大醫院需持續擴充醫學影像儲存與傳輸系統(Picture archiving and communication system,PACS)的儲存空間,且傳輸所需頻寬較大,亦對近年來隨著網際網路興盛而衍生出的雲端服務及遠距醫療造成發展阻礙。
醫學影像不同於一般日常影像,因為醫學影像關係到醫師診斷的正確性,其對影像品質的要求是高於一般影像的。大多數的醫學影像是由醫事技術人員操作醫學儀器取得影像後,提供醫師進一步判讀,在與病人病灶相關的關鍵性區域(Region of Interest,ROI)需保持無失真的影像品質,利於醫師做出正確診斷,以免誤判而造成後續醫療糾紛等事件;其他與病灶無關的非關鍵區域(Region of Non-Interest,RONI),如影像空白處、與病灶無關的部位等,由於對診斷較無直接關聯,可接受輕微失真的影像品質。以往有許多針對醫學影像相關的研究,如資訊隱藏、影像簽章、壓縮等技術,基本要求都是確保關鍵區域影像不失真,可見在醫學影像處理的領域裡,讓關鍵區域不失真已成為各種技術研究追求的目標。
多數的醫學影像壓縮處理技術中,只用單一壓縮方法處理整張影像,這樣會侷限了影像品質與檔案壓縮比率的變化彈性。在本篇論文中,我們以成人四肢骨骨折之X光影像為例:因X光影像屬灰階影像,且四肢骨影像關鍵區域位於骨頭組織邊緣,我們以門檻值法將影像二值化後,輔以像素擴展的概念,快速地將關鍵區域與非關鍵區域偵測區分出來。之後,將關鍵區域與非關鍵區域影像像素分別以JPEG2000進行無損及有損的影像壓縮處理。後續需要使用該影像時,只要分別將其解壓縮就可以取得影像品質與原圖相近、且關鍵區域沒有失真的重建影像,這顯示我們所提出的方法,可以達成保持關鍵區域影像品質與縮小儲存檔案所需空間的目標。
Recently, the digital medical image, e.g., PACS (Picture archiving and communication system), is more popular for diagnosis. To achieve the high diagnosis value, we need high resolution of these medical images. However, the more resolution will cause the more file size, and thus it will be not suitable for the medical clouding serviced and telemedicine.
The ROI (Region of Interest) is the key region of a medical image, and there should be no distortion to achieve the precise diagnosis. Other regions are so-called RONI (Region of Non-Interest. In this thesis, we consider a scheme which compresses the medical image to reduce transmission and storage. Here, we adopt distortion and distortion-less compression techniques for ROI and RONI respectively. Finally, we can get a better balance result between the image quality and compression ratio. Our scheme is a hybrid scheme with a dynamic ROI determination and using JPEG2000 compression with different ratios. Bone fracture image is tested in this thesis. We use the histogram technology to implement a dynamic expansion that we choose m-pixel expansion from the border of bone image. Using different compression ratios and different pixel expansions (m) are experimented. The results show that our scheme has the less image size and meantime has the distortion-less image in ROI when de-compressing the image.
Chapter 1 導論
1.1 研究背景
1.2 研究動機
1.3 研究目標
1.4 論文架構
Chapter 2 基本原理
2.1 數位影像
2.2 數位影像壓縮
2.3 數位影像壓縮效能評估
2.4 JPEG2000數位影像壓縮
2.4.1 JPEG2000基本介紹
2.4.2 JPEG2000特性介紹
2.4.3 JPEG2000編碼框架
2.4.3 JPEG2000相關應用
2.5 影像偵測與區域分割 ─ Otsu門檻值法
Chapter 3 結合有損與無損的醫學影像壓縮
3.1 關鍵區域動態偵測
3.2 關鍵區域範圍擴張
3.3 關鍵區域與非關鍵區域的區分
3.4 結合有損與無損的影像壓縮方法
3.5 影像品質驗證法
Chapter 4 實驗與分析
4.1 實驗
4.1.1 實驗環境
4.1.2 實驗流程
4.2 實驗結果與分析
4.2.1 實驗一:無關鍵區域像素擴展之影像壓縮與重建
4.2.2 實驗二:關鍵區域像素擴展1個像素之影像壓縮與重建
4.2.3 實驗三:關鍵區域像素擴展2個像素之影像壓縮與重建
4.2.4 實驗四:關鍵區域像素擴展3個像素之影像壓縮與重建
Chapter 5 結論與未來展望
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