Question

如何一次平均多个堆栈？理想情况下使用像ImageJ这样的GUI工具？我想在大约10-20个堆栈上执行此操作：1500x1500像素，500个切片，每个堆栈中有1个通道。一次加载所有这些将推动我的RAM的限制。

作为输出，我想要一个堆栈（1500x1500像素，500个切片，1个通道），并且在不同堆栈中平均强度。

ImageJ似乎限于一次平均2个堆栈。

我希望最终平均值中所有筹码的权重相等。

Answer 1

理想情况下使用像imageJ这样的GUI工具

有关ImageJ的用法且与任何代码无关的问题在stackoverflow.com上都是偏离主题的，应该最好在ImageJ forum上询问。

如何一次平均多个堆栈？

在ImageJ中，您可以从堆栈中构建 hyperstack （例如，使用 Image＆gt; Stacks＆gt; Tools＆gt; Concatenate ... 和然后 Image＆gt; Hyperstacks＆gt; Stack to Hyperstack ... ）并随后创建一个平均投影（ Image＆gt; Stacks＆gt; Z Project ... ）。要完成任务，您应该为每个堆栈分配500个切片到 t 维度，要平均的维度应该是 z 。

希望有所帮助。

Answer 2

我有太多的堆栈将它们全部组合成一个大的hyperstack。我的内存不足了。

我最终使用了python：

import tkFileDialog
import os
import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import glob
from tifffile import imsave

#select a directory containing tif-stacks to process
#tif-stacks must have equal dimensions

sd=tkFileDialog.askdirectory()

#list of files to process
fl= glob.glob(os.path.join(sd,'*.tif'))

#number of files to process
n_files=np.shape(fl)[0]

im = Image.open(fl[0])

#get number of frames in first file by seeking all frames until error occurs
#this seems clunky but is very fast
#assuming same number of frames for all files
n = 0
while True:
    n += 1
    try:
        im.seek(n)
    except:
        break
n_frames=n

#loop through all images,
#read each frame and accumulate frame-wise sum over all stacks

w, h = im.size
temp = np.zeros( (h,w,n_frames), dtype=np.int32 )

for i in range(n_files):
    print 'processing file: ', i
    im = Image.open(fl[i])

    for n in range (n_frames):
        curframe = np.array(im.getdata()).reshape(h,w)
        temp[:,:,n] += curframe
        im.seek(n)
        print ['frame: ', n],"         \r",

avgStack=temp/n_files

Answer 3

我稍微修改了jlarsch的代码，因为它没有在python3中运行。这是我的解决方案：

    from tkinter import filedialog
    import os
    from PIL import Image
    import numpy as np
    import glob
    from tifffile import imwrite, imread

    #select a directory containing tif-stacks to process
    #tif-stacks must have equal dimensions

    sd=filedialog.askdirectory()
    fl = glob.glob(os.path.join(sd, '*.tif'))

    #list of files to process
    fl= glob.glob(os.path.join(sd,'*.tif'))

    #number of files to process
    n_files=np.shape(fl)[0]
    #get number of frames in first file by seeking all frames until error occurs
    #this seems clunky but is very fast
    #assuming same number of frames for all files
    with Image.open(fl[0]) as im:
        h,w=im.size
        n = 0
        while True:
            n += 1
            try:
                im.seek(n)
            except:
                break
        n_frames = n

    #loop through all images,
    #read each stack and append to a 4-dimensional numpy array

    w, h = im.size
    temp = np.empty((0,n_frames,h,w), dtype=np.int32)
    for i in range(n_files):
        stack = imread(fl[i])
        temp = np.append(temp, stack[np.newaxis, :], axis=0)
    #average over all stacks
    average=np.mean(temp,axis=0)

    
    imwrite('average.tif', average)

多个堆栈的平均值

3 个答案: