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Yoshikatsu Sato, the head of microscope facility @NagoyaITbM presenting practicals #EMBOLivePlant https://t.co/SVrkfOKQCn
About 18 hours, 38 mins ago by: Kota Miura (@cmci_)

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Miyo Terao Morita showing analysis of gravitropism using centrifuge microscope they newly developed. I only know… https://t.co/Atj9E4QJAY
About 19 hours, 10 mins ago by: Kota Miura (@cmci_)

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@KeikoUTorii ... which then became the cover page of Development cell. convincing. https://t.co/XBgiqJpHog
About 20 hours, 8 mins ago by: Kota Miura (@cmci_)

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@KeikoUTorii model-based hypothesis lead to experiment results with single guard cell development or multiple >2 gu… https://t.co/oGhh4NJMPh
About 20 hours, 15 mins ago by: Kota Miura (@cmci_)

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now, @KeikoUTorii on stomata development - how very specific cell fate decisions are made, with proper spacing bet… https://t.co/XoR8tpB5WR
About 20 hours, 32 mins ago by: Kota Miura (@cmci_)

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@YvonJaillais talk on nanoclustering of ROP6, great analyses using various approaches to assess protein mobility… https://t.co/WHrzBsWTYJ
About 20 hours, 48 mins ago by: Kota Miura (@cmci_)
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CMCI weblog

ImgLib2, first test

I pretty much enjoyed ImageJ User and Developer conference 2012 in Luxemburg. Interesting people from different areas in science, very exciting to see how people are doing image processing and analysis. Some of live notes could be found in my time line. One of the great contribution for the third day was Bene Schmidt's work intseg_3D, combining user clicking and active contour fitting in 3D.

One of the core topic there was ImgLib2, the generic image typ behind ImageJ2. After coming back home, I tested ImgLib2 with the Jython code below.

Results were: Started testImgLib2.py at Sun Oct 28 16:41:57 CET 2012

  • ImgLib2 cursor 333 millisec
  • ImgLib2 for : 138 millisec
  • ImagePlus 152 millisec
  • ImageProcessor 114 millisec
  • Pixel Array 59 millisec

for loop using Img iterator is a bit faster than going through ImagePlus using classic nested for-loop. Even with the classic nested for-loop, using ImageProcessor was a bit faster than Img. The fastest is of course accessing pixels via pixel array. I only did this via ImagePlus, but there should be also some methods to extract an array from Img, which I did not test.

Addendum: See also proper benchmark in the following link in ImageJ2 site:

http://developer.imagej.net/imglib-benchmarks

Thanks to Albert Cardona for commenting on this.

# first trial with ImageLib2
# iterations

from net.imglib2.img import ImagePlusAdapter

imp = IJ.openImage("http://imagej.nih.gov/ij/images/blobs.gif")
img = ImagePlusAdapter.wrapReal(imp)

# accessing via ImagePlus
t3 = System.currentTimeMillis()
for i in range(imp.getHeight()):
	for j in range(imp.getWidth()):
#		print imp.getPixel(j, i)[0]
		imp.getPixel(j, i)[0]
				
t4 = System.currentTimeMillis()

# accessing via ImageProcessor
t5 = System.currentTimeMillis()
ip = imp.getProcessor()
for i in range(imp.getHeight()):
	for j in range(imp.getWidth()):
#		print ip.getPixelValue(j, i)
		ip.getPixelValue(j, i)
				
t6 = System.currentTimeMillis()

# ImgLib2 cursor
t1 = System.currentTimeMillis()
cursor = img.cursor()
cursor.fwd()
while cursor.hasNext():
	cursor.next()
#	print cursor.get()
	cursor.get()

t2 = System.currentTimeMillis()

t7 = System.currentTimeMillis()
for t in img:
#	print t.get()
	t.get()

t8 = System.currentTimeMillis()

# pixel array
t9 = System.currentTimeMillis()
pix = imp.getProcessor().getPixels()
for i in pix:
	i = i
#	print i

t10 = System.currentTimeMillis()	

print 'ImgLib2 cursor',(t2-t1), 'millisec'
print 'ImgLib2 for : ',(t8-t7), 'millisec'
print 'ImagePlus',(t4-t3), 'millisec'
print 'ImageProcessor',(t6-t5), 'millisec'
print 'Pixel Array',(t10-t9), 'millisec'
	

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blogtng/blogtop.txt · Last modified: 2016/05/24 05:46 (external edit)