博碩士論文 107827010 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:50 、訪客IP:3.144.244.44
姓名 蕭鉦澄(Jheng-Cheng Hsiao)  查詢紙本館藏   畢業系所 生物醫學工程研究所
論文名稱 舌紋分析的動態曝光方法
(Dynamic Multi-Scale Retinex for Tongue Image Analysis)
相關論文
★ 基於密度泛函理論的人體姿勢模態識別之非監督學習方法★ 整合Modbus與Websocket協定之聯網醫療資料採集嵌入式系統研製
★ 比較 U-net 神經網路與資料密度泛函方法對於磁共振影像分割的效能★ 使用YOLO架構在標準環境中進行動態舌頭影像偵測及切割
★ 使用YOLO辨識金屬表面瑕疵★ 使用深度學習結合快速資 料密度泛函轉換進行自動腦瘤切割
★ 使用強化學習模擬抑制新冠肺炎疫情★ 融合影像與加速度感測訊號的人體上部運動特徵視覺化之機械學習模型
★ 組建細胞培養人造磁場微實驗平台★ 標準CMOS製程之新型微機電麥克風驗證、濕式蝕刻加工製程開發暨量產製程研究
★ 靜磁場於癌細胞的生物效應★ 關節角度監測裝置應用在日常膝關節活動
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 舌診在中醫(TCM)中起著不可估量的作用,是中醫主要的診斷方法之一。通過中醫師以目視檢查舌頭及其特徵(包括活力,形狀,顏色,舌表層和水分)來進行檢查。這些信息本身或與舌頭影像圖譜的映射都可以幫助中醫醫生識別並確定患者體內的疾病。但是,舌診是根據醫生的知識和經驗來完成的,容易缺乏客觀的評估標準而可能會阻礙舌診的應用和有效性。隨著計算能力的提高和圖像處理技術的發展,技術上已經能在醫院中開發並使用了自動量化舌頭各層面的診斷設備。在這些技術優勢的基礎上,我們開發了一種基於人工智慧演算法的舌頭圖像辨識分割方法,該方法可以較容易辨識與分析目標舌頭的形態特徵,而不受時間和空間的限制。然而,為了實現這些任務,當代的人工智慧演算法遭受了諸如舌頭位置的干擾,光損傷或光污染以及色彩校正等困境。為了克服這些情況,我們通過將舌頭區域的長寬比和嘴唇的長度引入該方法,重新設計了傳統的舌頭圖像獲取方法。本方法可通過自動計算縱橫比來幫助用戶獲取正確的舌頭照片。然後,本論文將進一步採用Retinex演算法校正光的影響,包括光源的方向和每個光矢量的強度。因此,通過合併來自光向量的方向和強度的光信息,可以修改照片上RGB像素的強度。最終,將採用卷積數據密度泛函理論進行特徵提取和圖像分割。在臨床研究中,希望將來能從Landseed國際醫院的中醫診所收集大量舌頭照片,以建立雲數據庫,相關參與者和專家將幫助為監督的機器學習算法標記圖像。這項研究的期望結果是提供一種簡單的方法來連接舌頭形態和中醫應用。
摘要(英) Tongue diagnosis plays an invaluable role in Traditional Chinese Medicine (TCM) and is one of the major methods of diagnosis. It is performed by visual inspection of the tongue and its features, including vitality, shape, color, coating, and moisture. These pieces of information alone or mapping with the topographic regions of the tongue help a TCM doctor to identify and locate the disease in a patient’s body. However, tongue diagnosis is achieved based on the knowledge and experiences of a doctor, and the lack of objective evaluation standards may hinder the application and validity of tongue diagnosis. With the improvement of computing capability and the development of image processing technology, diagnostic equipment that automatically quantifies various aspects of tongues has been developed and used in hospitals. Under the foundation from these technical benefits, we developed a method of tongue image analysis based on artificial intelligence algorithms that allow easy monitoring and recognizing the morphological features of the targeted tongue without time and space limitations. However, in order to achieve these tasks, the contemporary AI algorithms suffer the predicaments, such as the disturbances of tongue position, light damage and/or pollution, and color correction, and so on. To overcome these circumstances, we redesign the conventional method of the tongue image acquisition by introducing the aspect ratio of the tongue area and length of lip into the method. The APP on the mobile phone will help users acquire correct tongue photos by calculating the aspect ratio. Then the Retinex algorithm will be employed to correct the effect of light, including the direction of the light source and the intensity of each light vector. Thus, the intensity of the RGB pixels on the photo would be modified by merging the light information from the directions and the intensities of the light vectors. On the clinical investigations, a large set of tongue photos will be collected from the TCM clinic of Landseed International Hospital to establish a cloud database, and relevant participants and experts will help label the images for the supervised machine learning algorithm. Eventually, the convolutional data density functional theory will be adopted for the feature extraction and image segmentation. The desired outcome of this study is to provide an easy methodology to connect the tongue morphologies and the TCM applications.
關鍵字(中) ★ 舌紋
★ 中醫
★ 影像處理
關鍵字(英) ★ Tongue
★ TCM
★ Image processing
論文目次 中文摘要               i
英文摘要               ii
致謝                 iii
目錄                 v
圖目錄                vi
一、   緒論            1
二、    理論發展與模擬       4
2-1 Hornc和Schunck光流法    4
2-1 圖像處理Retinex之增強算法 5
2-1-1 SSR             6
2-1-2 MSR             7
2-2 OTSU            9
2-3 色彩分割          10
三、 實驗架構          12
四、 研究內容與方法       16
3-1 研究方法與設計       16
3-2 環境布置之順序       16
3-3 演算法之結構        19
五、 結果與分析         23
六、 結論            30
七、 參考文獻          32
參考文獻 [1] Lo, L.-C., Cheng, T.-L., Chen, W.-J., Chen, Y.-F., and Chiang, J. Y. The Study on the Agreement between Automatic Tongue Diagnosis System and Traditional Chinese Medicine Practitioners. European Congress for Integrative Medicine (ECIM 2012), 2012.
[2] Zhen Qi,1 Li-ping Tu,1 Jing-bo Chen,2 Xiao-juan Hu,3 Jia-tuo Xu,1 and Zhi-feng Zhang1, The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine,indawi Publishing Corporation BioMed Research International Volume 2016, Article ID 3510807

[3] Zhang, H., Wang, K., Zhang, D., Pang, B., Huang, B. Computer aided tongue diagnosis system. The 27th IEEE International Conference of Engineering in Medicine and Biology Society, 2005.
[4] Kanawong, R., Computer-aided tongue image diagnosis and analysis. University of Missouri at Columbia Columbia, MO, Doctoral Dissertation, 2012.
[5] Joseph Solomon Friedman, History of color photography,1945

[6] Daniel J. Jobson, Zia-ur Rahman, and Glenn A. Woodell. Propertieis and performance of a center/surround retinex IEEE Transactaons on Image Processing. Submitted 1995.
[7] Zia-ur Rahman. Properties of a center/surround Retinex Part One: Signal processing design. NASA Contractor Report #198194, 1995.
[8] Daniel J. Jobson and Glenn A. Woodell. Properties of a center/surround Retinex Part Two: Surround design. NASA Technical Memorandum #110188, 1995.
[9] Z. Rahman, D. J. Jobson and G. A. Woodell, "Multi-scale retinex for color image enhancement," Proceedings of 3rd IEEE International Conference on Image Processing, Lausanne, Switzerland, 1996, pp. 1003-1006 vol.3, doi: 10.1109/ICIP.1996.560995.
[10] Kanawong, R., Xu, W., Xu, D., Li, S., Ma, T., and Duan, Y., An automatic tongue detection and segmentation framework for computer-aided tongue image analysis. Int. J. of Functional Informatics and Personalised Medicine. 4(1):56–68, 2012.
[11] Hongmin Cai, Zhong Yang, Xinhua Cao, Member, IEEE, Weiming Xia, and Xiaoyin Xu, Member, IEEE, A New Iterative Triclass Thresholding Technique in Image Segmentation, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 23, NO. 3, MARCH 2014

[12] Zhang, B., Wang, X., You, J., and Zhang, D., Tongue color analysis for medical application. Evid. Based Complement. Alternat. Med. 2013, 2013.
[13] Wang, X., and Zhang, D., A high quality color imaging system for computerized tongue image analysis. Expert Systems with Applications. 40(15):5854–5866, 2013.

[14] Min-Chun Hua,1 , Kun-Chan Lana,b,1 , Wen-Chieh Fangc,1 , Yu-Chia Huang d,1 , Tsung-Jung Ho b,e,f,1 , Chun-Pang Linf,1 , Ming-Hsien Yehd, Paweeya Raknima , Ying-Hsiu Lina , Ming-Hsun Chenga , Yi-Ting He g , Kuo-Chih Tsengg,h,1, Automated tongue diagnosis on the smartphone and its applications, January 4, 2018
[15] Min-Chun Hu1 & Ming-Hsun Cheng1 & Kun-Chan Lan1, Color Correction Parameter Estimation on the Smartphone and Its Application to Automatic Tongue Diagnosis, J Med Syst (2016) 40:18 DOI 10.1007/s10916-015-0387-z
[16] D. Sun, S. Roth and M. J. Black, "Secrets of optical flow estimation and their principles," 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, 2010, pp. 2432-2439, doi: 10.1109/CVPR.2010.5539939.
[17] N. Zhu, G. Wang, G. Yang and W. Dai, "A Fast 2D Otsu Thresholding Algorithm Based on Improved Histogram," 2009 Chinese Conference on Pattern Recognition, Nanjing, 2009, pp. 1-5, doi: 10.1109/CCPR.2009.5344078.
指導教授 陳健章(Chien-Chang Chen) 審核日期 2020-7-29
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明