R / ImageJ：测量点和曲线之间的最短距离 [英] R/ImageJ: Measuring shortest distance between points and curves

问题描述

我有一些R作为统计平台的经验，但对基于图像的数学缺乏经验。我有一系列照片（tiff格式，px /μm是已知的），带有孔和不规则曲线。我想测量一个孔与最接近的特定孔的曲线之间的最短距离。我想为照片中的每个洞做这个。这些洞也不规则，所以也许我需要告诉程序什么是洞和什么是曲线（ImageJ有一个点和分段线功能）。

任何想法如何做到这一点？我应该在R中使用哪个包？你会推荐另一个程序来完成这种任务吗？

解决方案

编辑：现在可以使用sclero软件包。该软件包目前在 GitHub 上提供，该过程在本教程。为了说明，我使用了一个来自教程的例子：

  library（devtools）
 install_github（MikkoVihtakari / sclero ，dependencies = TRUE）
 library（sclero）
 path<  -  file.path（system.file（extdata，package =sclero），shellspots.zip）
 dat<  -  read.ijdata（path，scale = 0.7812，unit =um）
 shell < -  convert.ijdata（dat）
 aligned<  -  spot.dist（shell）
 plot（aligned）
  

也可以使用sclero软件包提供的功能添加样本点大小。请参阅教程中的第2.5节。

I have some experience with R as a statistics platform, but am inexperienced in image based maths. I have a series of photographs (tiff format, px/µm is known) with holes and irregular curves. I'd like to measure the shortest distance between a hole and the closest curve for that particular hole. I'd like to do this for each hole in a photograph. The holes are not regular either, so maybe I'd need to tell the program what are holes and what are curves (ImageJ has a point and segmented line functions).

Any ideas how to do this? Which package should I use in R? Would you recommend another program for this kind of task?

解决方案

EDIT: Doing this is now possible using sclero package. The package is currently available on GitHub and the procedure is described in detail in the tutorial. Just to illustrate, I use an example from the tutorial:

library(devtools)
install_github("MikkoVihtakari/sclero", dependencies = TRUE)
library(sclero)
path <- file.path(system.file("extdata", package = "sclero"), "shellspots.zip")
dat <- read.ijdata(path, scale = 0.7812, unit = "um") 
shell <- convert.ijdata(dat)
aligned <- spot.dist(shell)
plot(aligned)

It is also possible to add sample spot sizes using the functions provided by the sclero package. Please see Section 2.5 in the tutorial.

这篇关于R / ImageJ：测量点和曲线之间的最短距离的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！