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		<title>k-Wave User Forum &#187; Topic: Reconstructing PAT data from a moving single-element transducer</title>
		<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer</link>
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		<pubDate>Wed, 13 May 2026 17:20:21 +0000</pubDate>
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			<title>Bradley Treeby on "Reconstructing PAT data from a moving single-element transducer"</title>
			<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer#post-6214</link>
			<pubDate>Sun, 12 Nov 2017 10:23:56 +0000</pubDate>
			<dc:creator>Bradley Treeby</dc:creator>
			<guid isPermaLink="false">6214@http://www.k-wave.org/forum/</guid>
			<description>&#60;p&#62;Perhaps a poor choice of phrase. If it's the same initial pressure distribution, but just sampled with your detector at a different point in space, then this is the normal case for photoacoustic tomography, and you should use a single reconstruction. There are some good review papers on photoacoustics if you need more details, including &#60;a href=&#34;http://www.medphys.ucl.ac.uk/research/mle/pdf_files/Review_Roy_Soc_Interface_1.pdf&#34;&#62;this one&#60;/a&#62;.&#60;/p&#62;
&#60;p&#62;Brad.
&#60;/p&#62;</description>
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		<item>
			<title>btshanahan on "Reconstructing PAT data from a moving single-element transducer"</title>
			<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer#post-6213</link>
			<pubDate>Fri, 10 Nov 2017 19:16:03 +0000</pubDate>
			<dc:creator>btshanahan</dc:creator>
			<guid isPermaLink="false">6213@http://www.k-wave.org/forum/</guid>
			<description>&#60;p&#62;It's not MxN measurements of the &#34;same data,&#34; if I'm understanding the term correctly - the transducer is moving relative to the object between measurements, so each location corresponds to a different initial pressure distribution.
&#60;/p&#62;</description>
		</item>
		<item>
			<title>Bradley Treeby on "Reconstructing PAT data from a moving single-element transducer"</title>
			<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer#post-6208</link>
			<pubDate>Fri, 10 Nov 2017 15:00:47 +0000</pubDate>
			<dc:creator>Bradley Treeby</dc:creator>
			<guid isPermaLink="false">6208@http://www.k-wave.org/forum/</guid>
			<description>&#60;p&#62;If you have taken MxN separate measurements of the same data, these should be reconstructed at the same time, i.e., one call to &#60;code&#62;kspacePlaneRecon&#60;/code&#62;, or one time reversal reconstruction.&#60;/p&#62;
&#60;p&#62;Brad.
&#60;/p&#62;</description>
		</item>
		<item>
			<title>btshanahan on "Reconstructing PAT data from a moving single-element transducer"</title>
			<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer#post-6207</link>
			<pubDate>Thu, 09 Nov 2017 06:04:48 +0000</pubDate>
			<dc:creator>btshanahan</dc:creator>
			<guid isPermaLink="false">6207@http://www.k-wave.org/forum/</guid>
			<description>&#60;p&#62;Hi Bradley,&#60;/p&#62;
&#60;p&#62;I would need to run &#60;code&#62;kspacePlaneRecon&#60;/code&#62; NxM times, once for each sensor location, no?&#60;/p&#62;
&#60;p&#62;Right now the data is in an NxMxNt matrix, but time-reversal presents the same issue - I can't just treat the MxN grid as an array, so I would need to do a time-reversal for each sensor location and then somehow recombine all NxM reconstructed images.
&#60;/p&#62;</description>
		</item>
		<item>
			<title>Bradley Treeby on "Reconstructing PAT data from a moving single-element transducer"</title>
			<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer#post-6199</link>
			<pubDate>Wed, 08 Nov 2017 14:00:57 +0000</pubDate>
			<dc:creator>Bradley Treeby</dc:creator>
			<guid isPermaLink="false">6199@http://www.k-wave.org/forum/</guid>
			<description>&#60;p&#62;Hi Brendan,&#60;/p&#62;
&#60;p&#62;I might be missing something, but why don't you collate your data into an MxNxNt matrix (where Nt is the number of time points), and then reconstruct your image using &#60;code&#62;kspacePlaneRecon&#60;/code&#62; or time reversal? In the latter, you could also account for the size of your detection elements in the reconstruction.&#60;/p&#62;
&#60;p&#62;Brad.
&#60;/p&#62;</description>
		</item>
		<item>
			<title>btshanahan on "Reconstructing PAT data from a moving single-element transducer"</title>
			<link>http://www.k-wave.org/forum/topic/reconstructing-pat-data-from-a-moving-single-element-transducer#post-6186</link>
			<pubDate>Fri, 03 Nov 2017 20:54:34 +0000</pubDate>
			<dc:creator>btshanahan</dc:creator>
			<guid isPermaLink="false">6186@http://www.k-wave.org/forum/</guid>
			<description>&#60;p&#62;I'm working on a project to improve our current PAT system and image-processing routine in particular, and I've hit a wall.&#60;/p&#62;
&#60;p&#62;We use a 6mm diameter, unfocused, 10 MHz transducer in a raster-scanning configuration in an imaging plane above the object. The issue I'm having is implementing the reconstruction after the data has been collected. In principle, if the imaging surface is a grid with NxM points, then image formation will involve NM separate reconstructions, all of which will then need to be combined to form a single image. And this is assuming that I can treat the initial pressure distribution as uniform throughout the data collection process (this assumption seems reasonable - the irradiation area is large relative to the size of the objects we typically study - but I'm not 100% convinced it's accurate). Then I will need to correct for imaging artifacts that result from the NxM separate limited FOV measurements. All of this seems prohibitively expensive computationally, and severely limited in terms of the accuracy and resolution we could hope to achieve even in the best case scenario.&#60;/p&#62;
&#60;p&#62;Has anybody implemented accurate single-element raster-scanning PAT imaging systems? I know the setup is common in PAM, but tomography introduces its own set of challenges.&#60;/p&#62;
&#60;p&#62;Thanks,&#60;br /&#62;
Brendan
&#60;/p&#62;</description>
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