# #——风格,eval = TRUE,呼应= FALSE,结果= "飞机 "-------------------------- BiocStyle:乳胶 () ## ---- 设置,包括= FALSE -------------------------------------------------- 库(knitr)美元opts_chunk组(无花果。path=" figexamplesegement /"， fig.show="hold"， fig.align="center"， out.width="0.35\\linewidth") ## ----eval=TRUE，包括= FALSE ---------------------------------------------- 图书馆(furrowSeg) # #——消息= FALSE --------------------------------------------------------- 数据(“exampleFurrowMovie”)img < - exampleFurrowMovie rm (exampleFurrowMovie) # #——segParm --------------------------------------------------------------- threshOffset < - 0.0005 px < - 0.293 filterSize < makeOdd(圆(microns2px (1 px = px))) L < - makeOdd(圆(microns2px (5 px = px))) minObjectSize < area2px (4px = px) maxObjectSize < - area2px (400 px = px) # #——gaussianSmoothing ----------------------------------------------------- z < - makeBrush(大小= filterSize形状=“高斯”,σ= filterSize / 2)显示(正常化(img[,, 1, 100]),方法=“光栅”)img2 < - filter2 (img, z)显示(正常化(img2[,, 1, 100]),方法= "光栅 ") ## ---- adaptiveThresholding -------------------------------------------------- 面具< -打(x = img2 (, 1), w = L / 2 h = L / 2,抵消= threshOffset)显示(面具,100,方法= "光栅 ") ## ---- maskSmoothing --------------------------------------------------------- 刷< - makeBrush(大小= filterSize形状=“盘”)面具< -关闭(面具,刷)面具< bwlabel面具(面具)< - furrowSeg::: filterObjects(面具,minObjectSize正)显示(面具(,100),方法= "光栅 ") ## ---- maskInversion --------------------------------------------------------- 面具< - furrowSeg::: invertMask面具(面具)< - fillHull面具(面具)< - furrowSeg::: filterObjects(面具,0,maxObjectSize)显示(面具(,100),方法= "光栅 ") ## ---- propagateSegmentation ------------------------------------------------- 面具< - reenumerate面具(面具)< -传播(img2(, 1),种子=面具)< - furrowSeg::: filterObjects面具(面具,minObjectSize maxObjectSize) h < - paintObjects (x =面具,tgt =正常化(img)坳=“黄色”)显示(hs(,, 1, 100),方法= "光栅 ") ## ---- comparisonToPackageFunction ------------------------------------------- x < - segmentFurrowAllStacks (x = img, L = L,filterSize=filterSize, threshOffset=threshOffset, closingSize=filterSize, minObjectSize=minObjectSize, maxObjectSize=maxObjectSize) all(mask == x$mask[[1]]) ## ----featureExtraction----------------------------------------------------- nt <- dim(mask)[3] getEBImageFeatures <- function(mask, ref) {xbw <- reenumerate(mask) fts <- computeFeatures(x=xbw, ref=ref, methods.noref=c("computeFeatures. mask ")moment"， "computeFeatures.shape")) return(fts)} ftList <- lapply(1:nt, function(t) {df <- getEBImageFeatures(mask[，， t]， img[，， 1, t]) df <- as.data.frame(df, stringsAsFactors=FALSE) df$t <- t return(df)}) fts <- do。调用(“rbind”,ftList) # #——APanisotropy ---------------------------------------------------------- fts $ e。X <- cos(fts$x.0 m.theta)*fts$x.0 m.theta。偏心# #——plotFeatures out.width = " 0.5 \ \线宽 "------------------------------ 框< - c(“xleft”= 64,“xright”= 448,“ybottom”= 128,顶端y = 384) fts < - isolateBoxCells (fts,盒子)plotFeatureEvolution (fts,达峰时间= 10,dt = 4.22/60, px = 0.293)