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computed tomography 三維圖像重建算法，該算法在二維ART基礎上改進所得
標簽： tomography computed 三維圖像 重建算法
上傳時間： 2014-01-15
上傳用戶：jichenxi0730
用于computed tomography 的算法測試計算投影數據的simpson積分函數
標簽： tomography computed simpson 算法
上傳時間： 2015-06-05
上傳用戶：dave520l
CT圖像金屬偽影消除技術的文獻。共3篇。 Reduction of Metal Artifacts in X-Ray computed Tomography XrayCT_artifacts Reduction of CT Artifacts Caused by Metallic Implants 由Willi A. Kalender, PhD Robert Hebel, Dipl Phys Johannes Ebersberger, Dr rer nat撰寫
標簽： XrayCT_artifacts Tomography Reduction Artifacts
上傳時間： 2013-12-06
上傳用戶：腳趾頭
computed distribution of the magnetic field Hz within an wvolving 2D dielectric mircopille with initial r=667nm run in COMSOL with Matlab
標簽： distribution dielectric mircopille computed
上傳時間： 2013-12-09
上傳用戶：zaizaibang
工業X-CT（X-ray computed Tomography）無損檢測技術是以不損傷或者破壞被檢測對象的一種高新檢測技術，被譽為最佳的無損檢測手段，在無損檢測領域日益受到人們的青睞。近年來，各國都在投入大量的人力、物力對其進行研究與開發。 目前，工業CT主要采用第二代和第三代掃描方式。在工業CT第三代掃描方式中，掃描系統僅作“旋轉”運動，控制系統比較簡單。對此，我國已取得了可喜的成績。然而，對工業CT系統中的二代掃描運動控制系統，即針對“平移+旋轉”運動的控制系統的研究，我國已有采用，但與發達國家相比，還存在較大的差距。二代掃描方式與其它掃描方式相比，具有對被檢物的尺寸沒有要求，且能夠對感興趣的檢測區域進行局部掃描的獨特優點。同時X光源的射線出束角較?。ㄒ话阈∮?0°），因此在工業X-CT系統主要采用二代掃描運動控制。有鑒于此，本論文結合有關科研項目，開展了工業X-CT二代掃描控制系統的研究。 論文首先介紹了工業X-CT系統的工作原理和各種掃描運動控制方式的特點，闡述了開展二代掃描控制的研究目的和意義。其次，根據二代掃描控制的特點，提出了“在優先滿足工業X-CT二代掃描控制的基礎上，力求實現對工業X-CT掃描運動的通用控制，使其能同時支持一、三代掃描方式”的設計思想。據此，研究確立了基于單片機AT89LV52及FPGA芯片EP1C3T100C8的運動控制架構，以實現二代掃描控制系統的設計方案。論文詳細介紹了可編程邏輯器件FPGA的工作原理和開發流程，并對其相關開發環境QuartusII4.1作了闡述。結合運動控制系統的硬件設計，詳細介紹了各功能模塊的具體設計過程，給出了相關的設計原理框圖和實際運行波形。并制作了相應的PCB板，調試了整個硬件控制系統。最后，論文還詳細研究了利用VisualC++6.0來完成上位機控制軟件的設計，給出了運動控制主界面及掃描運動控制功能軟件設計的流程圖。 論文對整個運動控制系統采用的經濟型的開環控制技術所帶來的不利影響，分析研究了增加步進電機的細分數以提高掃描精度的可能性，并對所研究的控制系統在調試過程中出現的一些問題及解決方案作了簡要的分析，提出了一些完善方法。
上傳時間： 2013-04-24
上傳用戶：stella2015
function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag) ％CUM2X Cross-covariance ％ y_cum = cum2x (x,y,maxlag, samp_seg, overlap, flag) ％ x,y - data vectors/matrices with identical dimensions ％ if x,y are matrices, rather than vectors, columns are ％ assumed to correspond to independent realizations, ％ overlap is set to 0, and samp_seg to the row dimension. ％ maxlag - maximum lag to be computed [default = 0] ％ samp_seg - samples per segment [default = data_length] ％ overlap - percentage overlap of segments [default = 0] ％ overlap is clipped to the allowed range of [0,99].
標簽： cum2x y_cum Cross-covariance function
上傳時間： 2015-09-08
上傳用戶：xieguodong1234
Each arc of a binary-state network has good/bad states. The system reliability, the probability that source s communicates with sink t, can be computed in terms of minimal paths (MPs). An MP is an ordered sequence of arcs from s to t that has no cycle. Note that a minimal path is different from the so-called minimum path. The latter is a path with minimum cost.
標簽： binary-state reliability probability network
上傳時間： 2015-12-04
上傳用戶：xcy122677
Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal ％ component subspace U of dimension PPCA_DIM using a centred covariance matrix X. The variable VAR contains the off-subspace variance (which is assumed to be spherical), while the vector LAMBDA contains the variances of each of the principal components. This is computed using the eigenvalue and eigenvector decomposition of X.
標簽： Probabilistic Components Principal Analysis
上傳時間： 2016-04-28
上傳用戶：qb1993225
OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.
標簽： OTSU segmentation Gray-level segmented
上傳時間： 2017-04-24
上傳用戶：yuzsu
The frequency domain plays an important role in image processing to smooth, enhance, and detect edges of images. Although image data typically does not include imaginary values, the fast Fourier transform (FFT) has been used for obtaining spectra. In this paper, the fast Hartley transform (FHT) is used to transform two-dimensional image data. Because the Hartley transform is real valued, it does not require complex operations. Both spectra and autocorrelations of two-dimensional ultrasound images of normal and abnormal livers were computed.
標簽： processing frequency important enhance
上傳時間： 2014-01-08
上傳用戶：1051290259
