This tool will separate the particles in terms of many parameters. And the
> Hello,
>
> It sounds like your images will likely have many variables – intensity,
> rotation angle, exact size and position of the section, etc. This will
> make it difficult to ‘forward’ engineer a macro by brute force estimation
> of variables. This sounds like a problem for a trainable machine learning
> classification algorithm. Fiji has a few options, most notably Trainable
> Weka Segmentation. If those do not do the job there are some more
> dedicated machine learning classification programs out there, including
> free ones like CellProfiler Analyst and AdvancedCellClassifier. As their
> names suggest they are meant for classifying cells, but the machine
> learning algorithms may be adaptable to your problem as well.
>
> Good luck!
>
>
> Tim
>
> Timothy Feinstein, Ph.D.
> Research Scientist
> Department of Developmental Biology
> University of Pittsburgh
>
>
>
>
> On 9/19/17, 12:54 AM, "ImageJ Interest Group on behalf of T Purushotham" <
>
[hidden email] on behalf of
[hidden email]> wrote:
>
> Respected to all,
> Greetings of the day. I have lot of case images of fetal echo with
> different types like four chamber view, LVOT, RVOT, Three vessel view and
> Three vessel arch view.Now, I want to develop a macro or algorithm in such
> a way that, whenever I upload the image it can automatically identifies
> the image whether it belongs to which type in above mentioned five cases.
> Can anyone help me to move forward in this. Also,
> how far this ImageJ/Fijji useful for me to overcome my problem. Mention any
> new Machine Learning strategies to solve this.
>
> Thanks and Regards,
> T Purushotham,
> IIT- Madras.
>
>
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