http://imagej.273.s1.nabble.com/Frequency-Filtering-in-Time-Dimension-tp5021367p5021391.html
real-time. That's the only fact we need to understand what I've written
except in its semantic interpretation. That's what you like to do but it
temporal. However, if it is finished and you've stored the data, then it
> Herbie...
>
> There are more things in heaven and earth, Horatio,
> Than are dreamt of in your philosophy.
> - Hamlet (1.5.167-8), Hamlet to Horatio
>
> Depending on the time frame that you are concerned with will dictate if you
> look at your data as temporal. From the image acquisition perspective your
> view has merit. Although, from the study of what is contained in these
> sequential volumes of images, e.g., data points, they may very well be
> temporal.
>
> In MRI:
>
> fMRI and perfusion are real time data that monitors physiological processes as
> they occur, and, are analyzed as temporal signals.
>
> MRE(lastography) are real time data in which the subject of the images is
> perturbed in real time and the response, i.e., the images, are analyzed as
> temporal responses.
>
> B0 map, T1 map, T2 map, the independent variable is time, but not real time,
> albeit, temporal analysis tools are applicable.
>
> Diffusion data is varied by magnetic gradient field strength and timing
> parameters, temporal analysis tools are applicable.
>
> I could go on, but suffice it to say that ImageJ is very useful to examine
> this data in the frame dimension, and there is a lot on untapped functionality
> that can be provided here...
>
> Thanks for listening,
>
> Fred
>
>
> On Thu, November 1, 2018 11:50 am, Herbie wrote:
>> Jacob,
>>
>> I didn't want to imply this:
>>
>> "It seems that you are saying that ImageJ is limited in scope to static
>> images"
>>
>> What I had in mind are real-time signals.
>>
>> "Have I misunderstood you?"
>>
>> Yes.
>>
>> ImageJ isn't capable of dealing with real-time temporal signals.
>>
>> If you have a temporal sequence of images available, the sequence is no
>> longer temporal, it is a static stack of images and all the problems
>> occurring with causal temporal processing are irrelevant because the
>> stack of images is a-causal from an signal processing point of view. Of
>> course you know that e.g. slice 2 comes before slice 3 but it is no
>> problem to have e.g. a convolution kernel that extends from slice 1 to
>> slice 5. In real-time processing this isn't possible as long as slice 5
>> is available...
>>
>> I hope this makes things a bit clearer.
>>
>> Regards
>>
>> Herbie
>>
>> ::::::::::::::::::::::::::::::::::::::::::
>> Am 01.11.18 um 16:40 schrieb Jacob Keller:
>>> Because here and with ImageJ we deal with images,
>>> filter-characteristics
>>> that are typical for the processing of causal time-signals don't play a
>>> role and I don't think that they are or will be implemented for use
>>> with
>>> ImageJ.
>>>
>>>
>>> It seems that you are saying that ImageJ is limited in scope to static
>>> images? Huh? I see a lot of folks using it for time series, and there
>>> are quite a few plugins that incorporate time. I have noticed generally
>>> a bit of a split in the community regarding time series, but it seems to
>>> me that time is a critical component of biological processes, and at the
>>> level of microscopy is quite accessible, so why limit imageJ to static
>>> images? Have I misunderstood you?
>>>
>>> Jacob
>>>
>>>
>>
>> --
>> ImageJ mailing list:
http://imagej.nih.gov/ij/list.html>>
>
>