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系所資訊
高怡宣 教授

高怡宣 教授

美國威斯康辛大學,物理博士

專長:磁振影像、醫學影像處理
辦公室:實驗大樓 B312 室
電話:(02)2826-7229(office) (02)2826-7000 #5803(lab)
電子信箱:yhkao@ym.edu.tw
諮詢時間:週三 10:10 ~ 12:00
個人網站:
https://sites.google.com/view/yhkao


 

研究領域

研究領域-高怡宣 教授

 

研究興趣

  磁振影像所觀察的訊號來源,主要是人體水份的氫核子。磁振造影的原理是﹕人體放在一個靜磁場中,體內水份中的氫核子會產生類似小磁鐵的磁雙矩 (magnetic dipole),並有旋進 (precessing) 的現象。由法拉第定律可知,磁通量的改變,會產生感應電動勢,類似於發電機的大磁鐵在旋轉時,可以產生電力。因此,藉由導電的線圈接受磁雙矩旋進的訊號,再利用數學的傅利葉轉換 (Fourier Transform),即可建造出磁振影像。磁振影像對於腦部的軟組織(例如灰質、白質),病灶(例如腫瘤、水腫、局部缺血),和血管病變等,都能提供很明確的診斷資訊。
  腦部組織所需的氧氣和養分,是經由動脈血液灌注 (perfusion) 到微血管網路所提供。因此,一個非侵入性的影像技術,對於觀測腫瘤及中風等病人的局部血流供應是很重要的。我們的研究興趣,即是以磁振影像,研究人類腦部的血流灌注狀況。我們以注射對比劑及動態磁振造影的方式,記錄對比劑在通過生理組織時,所造成的訊號改變。應用統計理論及電腦軟體,分析腦部不同部位血管的供血狀況,並計算相對大腦血體積、相對大腦血流量、及平均穿流時間的參數影像。
  另一個研究方向為觀察腦脊髓液 (cerebrospinal fluid) 的脈動情形,腦脊髓液會受到心跳及呼吸的調控,藉由心電圖收集心跳訊號,並以腹部的壓力皮帶來獲取呼吸訊號,來區別正常呼吸和閉氣下的訊號-時間曲線,再運用統計分析方法來分析呼吸及心跳訊號在腦脊髓液的傳遞情形,希望未來可運用於臨床上提供腦脊髓液異常現象的診斷資訊。

實驗室成員

碩士班 (入學年度)

  1. 胡明欽-中國醫藥大學醫放系畢業(102)
  2. 張智凱-中國醫藥大學醫放系畢業(102)
  3. 江蓮-陽明大學醫放系畢業(101)
  4. 王嫥嫥-高雄醫學大學醫放系畢業(100)

學術著作

期刊論文
  1. Kao YH, Guo WY, Liou AJK, Chen TY, Huang CC, Chou CC, Lirng JF. Transfer function analysis of respiratory and cardiac pulsations in human brain observed on dynamic magnetic resonance images. Computational and Mathematical Methods in Medicine Vol. 2013, Article ID 157040, 7 pages (2013). (SCI) PDF
  2. Teng MMH,Cho IC, Kao YH,* Chuang CS, Chiu FY, Chang FC. Improvements in the quantitative assessment of cerebral blood volume and flow with the removal of vessel voxels from MR perfusion images. BioMed Research International Vol. 2013, Article ID 382027, 11 pages (2013). (SCI) *: corresponding author. PDF
  3. Kao YH, Teng MMH, Zheng WY, Chang FC, Chen YF. Removal of CSF pixels on brain MR perfusion images using first several images and Otsu’s thresholding technique. Magnetic Resonance in Medicine 64:743–748 (2010). (SCI)
  4. Kao YH, Teng MMH, Zheng WY, Chang FC, Chen YF. Removal of CSF pixels on brain MR perfusion images using first several images and Otsu’s thresholding technique. Magnetic Resonance in Medicine (2010). (SCI) (in press)
  5. Kao YH, Teng MMH, Liu KC, Lam IP, Lin YC.. Hemodynamic segmentation of MR perfusion images in patients with unilateral carotid stenosis using independent component analysis. JOURNAL OF MAGNETIC RESONANCE IMAGING 2008;28:1125-1132 (SCI).
  6. Kao YH, Guo WY, Liou AJK, Hsiao YH, Chou CC.. The respiratory modulation of intracranial cerebrospinal fluid pulsation observed on dynamic echo planar images. Magnetic Resonance Imaging 2008;26:198-205 (SCI).
  7. Guo WY, Wu YT, Wu HM, Chung WY, Kao YH, et al.. Toward normal perfusion after radiosurgery: perfusion MR imaging with independent component analysis of brain arteriovenous malformations. American Journal of Neuroradiology 2004;25:1636-44 (SCI).
  8. Kao YH, Guo WY, Wu YT, et al.. Hemodynamic segmentation of MR brain perfusion images using independent component analysis, thresholding, and Bayesian estimation. Magnetic Resonance in Medicine 2003;49:885-894 (SCI).
  9. Teng MMH, Cheng HC, Kao YH, et al.. MR perfusion studies of brain for patients with unilateral carotid stenosis or occlusion: evaluation of maps of "time to peak" and percentage of baseline at peak. Journal of Computer Assisted Tomography 2001;25(1):121-125 (SCI).
  10. Hwang YS, Kao YH, Cheng HC, Teng MMH.. Cerebral perfusion study using MR images. Chinese Journal of Radiologic Technology 2001;25:149-158 (OI).
  11. Kao YH, MacFall JR, Wan X.. Correction of MR k-space data corrupted by spike noise. IEEE Transactions on Medical Imaging 2000;19(7):671-680 (SCI).
  12. Kao YH, Winkler SS, Baker EH, Turski PA, Chu WC. A post-processing method for displaying vessels from routine fast-spin-echo images: MRI-derived angiography. Magnetic Resonance Imaging 1999;17(7):1057-1063 (SCI).
  13. Kao YH, Wan X, MacFall JR.. Simultaneous Multislice Acquisition with aRterial-flow Tagging (SMART) using Echo Planar Imaging (EPI). Magnetic Resonance in Medicine 1998;39(4):662-665 (SCI).
  14. Kao YH, Sorenson JA, Winkler SS.. MR image segmentation using vector decomposition and probability techniques: a general model and its application to dual-echo images. Magnetic Resonance in Medicine 1996;35(1):114-125 (SCI).
  15. Kao YH, Sorenson JA, Bahn MM, Winkler SS.. Dual-echo MRI segmentation using vector decomposition and probability techniques: a two-tissue model. Magnetic Resonance in Medicine 1994;32(3):342-357 (SCI).