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醫療影像處理在診斷上之應用

醫療影像處理在診斷上之應用. 嘉義大學資工系 教授 柯建全 時間 : 2009 年 5 月 13 日. Outline. Introduction Object of medical image processing Imaging devices applications Related techniques for Medical imaging Research Results Future works. Introduction. What is Medical imaging?

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醫療影像處理在診斷上之應用

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  1. 醫療影像處理在診斷上之應用 嘉義大學資工系 教授 柯建全 時間: 2009年5月13日

  2. Outline • Introduction • Object of medical image processing • Imaging devices • applications • Related techniques for Medical imaging • Research Results • Future works

  3. Introduction • What is Medical imaging? • Why do we need digital image processing? • What kind of problems are often caused in medical images? • Blurring caused by respiratory or motion • Low contrast caused by imaging device or resolution • Complicated textures • Research trends have been transferred from 2-D to 3-D reconstruction

  4. Introduction (continue) • Integrate all possible methods in the filed of DIP, pattern recognition, and computer graphics • Qualitative • Quantitative • Three categories of imaging in different modalities • Structural image • Functional image • Molecular image

  5. Object • Help physicians diagnose • Reduce inter- and intra-variability • Produce qualitative and quantitative assessment by computer technologies • Determine appropriate treatments according to the analyses • Surgical simulation or skills to reduce possible erros

  6. Medical Imaging Modalities • X-ray • Ultrasound: non-invasive • Computed tomography • Magnetic resonance imaging • SPECT (Single photon emission tomography) • PET( Positron emission tomography) • Microscopy

  7. X-ray

  8. Ultrasound • 2-D sonography • 3-D sonography • Doppler color sonography • A series of 2-D projection • Reconstruction • 4-D sonography

  9. Computed tomography

  10. MRI • 可以觀察活體三度空間的斷層影像 • 磁振影像取影像時可以適當控制而得到不同參數的影像，如溫度、流場(flow)、水含量、分子擴散( diffusion)、 灌流(perfusion)、化學位移(chemical shift)、功能性(functional MRI) 及不同核種如氫、碳、磷

  11. MRI-structural and functional image

  12. Related techniques • Image processing • Segmentation • Registration • Feature Extraction • Shape feature • Texture • Motion tracking • Pattern recognition • Supervised learning • Un-supervised learning • Neuro network • Fuzzy • Support vector machine(SVM) • Genetic algorithm

  13. Related techniques • 3-D graphic • Virtual diagnose or visualization • Fusion between different modalities • Bio-medical visualization

  14. SPECT-functional image

  15. PET(Positron Emission Tomography ) • PET以分子細胞學為基礎，將帶有特殊標記的葡萄糖合成藥劑注入受檢者體內，利用PET掃瞄儀的高解析度與靈敏度作全身的掃描，藉由癌細胞分裂迅速，新陳代謝特別旺盛，攝取葡萄糖達到正常細胞二至十倍，造成掃描圖像上出現明顯的「光點」 • 能於癌細胞的早期(約0.5公分)準確地判定癌細胞，提供醫師作為診斷及治療的依據，診斷率高達87-91％，30歲以上的成年人及有癌症家族史的民眾，建議每隔1～2年做一次PET檢查。

  16. PET (Positron emission tomography)

  17. Applications in a hospital • Assist surgeon plan surgical operation or diagnose • Picture archiving system (PACS) • 將醫療系統中所有的影像，以數位化的方式儲存，並經由網路傳遞至同系統中，供使用者於遠側電腦螢幕閱讀影像並判讀。 • Telemedicine • Surgical simulation: Medical Visualization，Surgical augmented Reality, Medical-purpose robot, Surgery Simulation，Image Guided Surgery，Computer Aided Surgery • Estimate the location, size and shape of tumor

  18. PACS System

  19. Virtual Surgery

  20. Related techniques • Classification of normal or abnormal tissues such as carcinoma • Pre-processing: Contrast enhancement, noise removal, and edge detection • Lesion segmentation: extract contours of interest • thresholding • 2-D segmentation • 3-D segmentation based on voxel data • Color image processing

  21. Our study • Contour detection and blood flow measurements in cardiac nuclear medical imaging • Virtual colonoscopy • Bone tumor segmentation with MRI and virtual display • Breast carcinoma based on histology

  22. 原始 系列影像 影像放大 影像強化 影像去雜訊 左心室輪廓偵測 心室功能計算 影像前處理

  23. (a)強化後影像 (b)心臟血流變化區域 (c)心臟區域輪廓

  24. Background Region

  25. Contours within a sequence of frames

  26. Result Tab4.1 心室功能量測參數

  27. Virtual colonscopy-Browsing or navigation within a colon • Helical CT –patients injected contrast medium • Re-sampling—Voxel-based • Interpolation • Automatic segmentation (seed) • threshloding • Determination of the skeleton of the colon • Connected-Component Labeling • Surface rendering and volume rendering • Extraction of suspicious sub-volumes for diagnosis

  28. Automatic segmentation

  29. Determination of the skeleton of the colon

  30. Display and measurement

  31. Bone tumor segmentation with MRI and virtual display—Contrast medium • Otsu thresholding • Region growing • Tri-linear interpolation • Morphological post-processing • Surface rendering • Measurement

  32. Histogram of T1 weighted and T2 weighted

  33. (a) 0度(b) 45度 (a) 0度(b) 45度

  34. Classification of Breast Carcinoma

  35. Automatic and less human interaction Qualitative and quantitative measurements Stable and reliable (experiments with much more cases) Performance evaluation True positive, true negative, false positive, false negative Accuracy, sensitivity, and specificity Receiving operating characteristic curve (An index for evaluating the effectiveness of classification Optimal classification threshold Area under ROC approach 1 – better classification Requirements for medical image processing system in clinical diagnosis

  36. ROC curve

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