## ----style, eval=TRUE, echo=FALSE, results="asis"-------------------------- BiocStyle::latex() ## ----setup, include=FALSE-------------------------------------------------- library(knitr) opts_chunk$set(fig.path="figExampleSegmentation/", fig.show="hold", fig.align="center", out.width="0.35\\linewidth") ## ----eval=TRUE, include=FALSE---------------------------------------------- library(furrowSeg) ## ----message=FALSE--------------------------------------------------------- data("exampleFurrowMovie") img <- exampleFurrowMovie rm(exampleFurrowMovie) ## ----segParm--------------------------------------------------------------- threshOffset <- 0.0005 px <- 0.293 filterSize <- makeOdd(round(microns2px(1, px=px))) L <- makeOdd(round(microns2px(5, px=px))) minObjectSize <- area2px(4, px=px) maxObjectSize <- area2px(400, px=px) ## ----gaussianSmoothing----------------------------------------------------- z <- makeBrush(size=filterSize, shape="gaussian", sigma=filterSize/2) display(normalize(img[, , 1, 100]), method="raster") img2 <- filter2(img, z) display(normalize(img2[, , 1, 100]), method="raster") ## ----adaptiveThresholding-------------------------------------------------- mask <- thresh(x=img2[, , 1, ], w=L/2, h=L/2, offset=threshOffset) display(mask[, , 100], method="raster") ## ----maskSmoothing--------------------------------------------------------- brush <- makeBrush(size=filterSize, shape="disc") mask <- closing(mask, brush) mask <- bwlabel(mask) mask <- furrowSeg:::filterObjects(mask, minObjectSize, Inf) display(mask[, , 100], method="raster") ## ----maskInversion--------------------------------------------------------- mask <- furrowSeg:::invertMask(mask) mask <- fillHull(mask) mask <- furrowSeg:::filterObjects(mask, 0, maxObjectSize) display(mask[, , 100], method="raster") ## ----propagateSegmentation------------------------------------------------- mask <- reenumerate(mask) mask <- propagate(img2[, , 1, ], seeds=mask) mask <- furrowSeg:::filterObjects(mask, minObjectSize, maxObjectSize) hs <- paintObjects(x=mask, tgt=normalize(img), col="yellow") display(hs[, , 1, 100], method="raster") ## ----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.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$t <- t return(df) }) fts <- do.call("rbind", ftList) ## ----APanisotropy---------------------------------------------------------- fts$e.x <- cos(fts$x.0.m.theta)*fts$x.0.m.eccentricity ## ----plotFeatures, out.width="0.5\\linewidth"------------------------------ box <- c("xleft"=64, "xright"=448, "ybottom"=128, "ytop"=384) fts <- isolateBoxCells(fts, box) plotFeatureEvolution(fts, tMax=10, dt=4.22/60, px=0.293)