how to detect infected region in medical image say cancer or malaria parasites using microscopic images?
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how to detect infected region in medical image say cancer or malaria parasites using microscopic images?
1 Kommentar
Image Analyst
am 21 Aug. 2013
Bearbeitet: Image Analyst
am 21 Aug. 2013
No one's answer makes much sense now that you've replaced your original question with this one. And you never accepted any of those original answers so maybe I'll just wait for that. Actually, you already have started a new question on this totally new topic in a separate posting, so you didn't even need to edit/destroy this one. So go ahead and accept one answer below.
Antworten (3)
Image Analyst
am 3 Aug. 2011
If you want less noise, obviously. What other need would you have?
1 Kommentar
Sean de Wolski
am 4 Aug. 2011
+1
The only other need I can think of is to get an A in the class.
median(['A-' 'A+' 'A' ])
Pierre
am 4 Aug. 2011
Jan, I agree with you, the question is very surprising. Especially the required effort in typing in a question and a title on MATLAB Answers instead of looking up only a few key words on Google and getting instant answers "off-the-shelf" from wikipedia for example.
Jalari, on wiki you find couldn't miss the article about image noise. Now, deviated from your other questions (in which you seem trying to make other people do your work - I might be wrong but this is the image I got so far), you haven't had any look on basic signal processing although, regarding your task, you definitely should have so; I'll point out that very often (and obviously in your case) one is interested in the edges in an image as those are the most obvious entities containing information. Therefore, linear noise-reduction filters as the Gaussian smoothing filter are not always best suited for this purpose as they reduce significance of edges at the same time. An alternative to linear filters though are non-linear filters as is the Median filter which does reduce high-frequency noise in mostly uniform regions while preserving edges to a much better extent. It is very popular amongst non-linear filters, as it can be implemented very efficiently compared to other filters in this class.
If you cannot find an answer through google, you may still ask your question here, but the fact, that google yields very accurate answers on your question with the very first links is quite offending to me.
Cheers
0 Kommentare
Jan
am 3 Aug. 2011
This is a surprising question. Do you want to know, why any filter is applied at all, or what the benefits of the median filter are?
0 Kommentare
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