Parte I. Introducción a ImageJ Parte II – Operaciones sobre píxeles Parte III - Filtros Parte IV - Análisis de imágenes
Parte I. Introducción a ImageJ Parte II – Operaciones sobre píxeles Parte III - Filtros Parte IV - Análisis de imágenes
Spots.tiff: Image courtesy of Wu Yuhong: 1. It is RGB 2. Low contrast 3. Uneven background (stripes from a scanner) 4. Size is given as 1.54x1.18 inches
The goal is to count, and measure the spots. The approach has to evolve, but here are the essential elements: 1. Since all of the spots appear to be black, color is not
significant, and one can use a monochrome image. 2. The background must be dealt with. 3. The spots need to be discriminated from the
background –several options. 4. We can scan a line across the image, storing the
coordinates.
Note the slight rise upwards, Also the range, from 140-ish to 130 or so for the largest dot.
Adjust contrast and brightness according to the histogram
Separate channels
red
green
blue
It appears that the greatest difference between the background and the signal is in the red channel, but there are stripes on the image.
Scan each channel.
red
green
blue
It appears that the greatest difference between the background and the signal is in the red channel, but there are stripes on the image.
Red channel
We make a rough determination of the threshold.
Exclude very small objects by selecting a size > 10
La transformada de Fourier se puede usar, entre otras cosas, para eliminar ruido periódico. También para realizar filtrados de suavizado o de realce.
La transformada de Fourier se puede usar, entre otras cosas, para eliminar ruido periódico. También para realizar filtrados de suavizado o de realce. http://imagej.nih.gov/ij/docs/guide/146-29.html#toc-Subsection-29.10
Bandpass Filter to smooth background
FFT Filtering
Here is one of the nifty
things you may use fft
filtering for. The laser
scanning confocal
microscope scans along
the X axis. If there is
noise in the laser, then
this shows up most
dramatically in adjacent X
axis scans. Filtering the
frequency of the
alternating X axis
intensities cleans up the
image.
FFT filtering example
Recursos usados para la elaboración de estas diapositivas:
» ImageJ, A Useful Tool for Image Processing and Analysis Joel B. Sheffield, Temple University.
http://rsbweb.nih.gov/ij/docs/examples/IJ-M&M08.ppt
» MRI ImageJ Workshop. Exercises 4 with solutions
http://dev.mri.cnrs.fr/wiki/imagej-workshop
» http://rsb.info.nih.gov/ij/docs/examples/FFT/index.html
» Operaciones morfológicas binarias
» Operaciones morfológicas binarias
» Operaciones morfológicas binarias
Original erosión
apertura= erosión+dilatación
clausura= dilatación+erosión
dilatación
Ejercicio Usa todo lo aprendido sobre Image J para intentar segmentar la imagen de células de músculo humano.
Consulta los trabajos en https://opera.eii.us.es/pid