查詢結果分析
相關文獻
- A Fourier-Domain Maximum Likelihood Estimator and Its Application to Fractal Analysis of Medical Images
- Fractal Analysis and Its Application to Image Analysis
- A Maximum Likelihood Estimator and Fractal Analysis of Medical Images
- Fractal Analysis of Self-Similar Textures Using Wigner-Ville Distribution
- A Paley-Wiener Theorem for Distributions with Nonconvex Compact Supports
- 設計DMT ADSL Transceiver類比前端(AFE)之考量
- 傅立葉轉換紅外光譜儀石化工業區空氣污染監控
- The Potential Flow Field Generated by the Flanged Hood Openings of Various Shapes
- 電顯及紅外光譜應用於塗布紙塗層結構分析
- 以碎形為基礎的內插模式與雙線性、立方迴旋內插的比較
頁籤選單縮合
題名 | A Fourier-Domain Maximum Likelihood Estimator and Its Application to Fractal Analysis of Medical Images=傅立葉最大可能性估計與其在醫學影像上之碎形分析 |
---|---|
作者 | 溫哲彥; Wen, Che-yen; |
期刊 | 弘光學報 |
出版日期 | 19981000 |
卷期 | 32 1998.10[民87.10] |
頁次 | 頁145-158 |
分類號 | 410.01344 |
語文 | eng |
關鍵詞 | 碎形; 醫學影像分析; 最大可能性估計; 傅立葉; Fractals; Textures; Fourier-domain; Maximum likelihood estimator; |
中文摘要 | B.B.Mandelbrot於1967年所提出的;碎形“(Fractals)”概念,近年來已被廣 泛地應用在各種領域。在碎形分析的過程中,最重要的是測量所謂的碎形空間度( Fractal Dimension ), 或“碎形參數 H ”。 相對於傳統的歐幾里得空間度( Euclidean Dimension )的整數值,碎形空間度則可以是非整數值。“碎形”理論已被用來分析許多“ 自然性”的紋路影像。在所有的碎形數學模式中,“碎形布朗運動”扮演著重要的角色,並 且已被用來分析“自我相似”紋路影像。 最大可能性估計( Maximum Likelihood Estimator; MLE )被認為能有效地用來計算碎形空間度,然而,此方法需要大量的計算。 在 本文中,我們提出傅立葉最大可能性估計( Fourierdomain Maximum Likelihood Estimator; FMLE )來計算碎形空間度,並利用“碎形”實驗影像與真實人類骨骼核共振影 像來測試我們的方法。 |
英文摘要 | In using the fractal model, the most important procedure is to measure the fractal parameter H (or the Hurst coefficient ), which is directly related to the fractal dimension (or the Hausdorff Besicovitch dimension). The morphology of trabecular bone can be evaluated by the fractal analysis method. Recently, it has been applied to evaluate images with a varying range of gray levels, such as bone radiographic images. The Maximum Likelihood Estimator (MLE) is considered to be the optimal estimator for the fractal parameter H, since probability density function (PDF) of Fractional Brownian Motion (FBM) is known. Much of the work done so far has concentrated in the spatial domain. In this paper, we propose an approximate MLE method for estimating H in the Fourier domain. This method saves computational time and can be applied to estimating the parameter H directly from the Fourier-domain raw data collected by the Magnetic Resonance Imaging (MRI) scanner. We use synthetic fractal datasets and a human tibia image to study the performance of our method. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。