<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head>
<body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
Hello Jonas,
<div class=""><br class="">
</div>
<div class="">So ITK ( and therefore SimpleITK ), by default multi-thread each filter by default. This enables efficient processing of larger images.</div>
<div class=""><br class="">
</div>
<div class="">However, for your task you can run a large number of filters concurrently. Fortunately, SimpleITK does support concurrent execution of ITK filters with light weight python Threads! This is an uncommon feature for Python libraries and is a distinguishing
feature of SimpleITK.</div>
<div class=""><br class="">
</div>
<div class="">I have been planning on writing an example or notebook on this. Here is an efficient and compact code to accomplish your task as I understand it:</div>
<div class=""><br class="">
</div>
<div class="">
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">import SimpleITK as sitk</span></div>
</div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">
<div style="margin: 0px; line-height: normal;" class=""><span style="font-variant-ligatures: no-common-ligatures" class="">from multiprocessing.pool import ThreadPool</span></div>
<div style="margin: 0px; line-height: normal;" class=""><span style="font-variant-ligatures: no-common-ligatures" class=""><br class="">
</span></div>
<div style="margin: 0px; line-height: normal;" class=""><span style="font-variant-ligatures: no-common-ligatures" class="">p = ThreadPool()</span></div>
<div class=""><span style="font-variant-ligatures: no-common-ligatures" class=""><br class="">
</span></div>
<div class=""><span style="font-variant-ligatures: no-common-ligatures" class=""># <a href="https://github.com/blowekamp/itkOBBLabelMap/tree/master/test/data" class="">https://github.com/blowekamp/itkOBBLabelMap/tree/master/test/data</a></span></div>
</span></div>
<div class="">
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">img = sitk.ReadImage(“~/Downloads/jelly_beans.png")</span></div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">seg = sitk.ReadImage(“~/Downloads/jelly_beans_seg.png”)</span></div>
</div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class=""><br class="">
</span></div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">shapeStats = sitk.LabelShapeStatisticsImageFilter()</span></div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">shapeStats.Execute(seg)</span></div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class=""><br class="">
</span></div>
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">
<div style="margin: 0px; line-height: normal;" class=""><span style="font-variant-ligatures: no-common-ligatures" class="">def extract_bb(img, shape_stats_filter, label):</span></div>
<div style="margin: 0px; line-height: normal;" class=""><span style="font-variant-ligatures: no-common-ligatures" class=""> [x,y,xsize,ysize]=shape_stats_filter.GetBoundingBox(label)</span></div>
<div style="margin: 0px; line-height: normal;" class=""><span style="font-variant-ligatures: no-common-ligatures" class=""> return sitk.RegionOfInterest(img,size=[xsize,ysize],index=[x,y])</span></div>
</span></div>
<div class=""><br class="">
</div>
<div class="">
<div style="margin: 0px; font-size: 11px; line-height: normal; font-family: Menlo;" class="">
<span style="font-variant-ligatures: no-common-ligatures" class="">bbimg_list = p.map(lambda label: extract_bb(img, shapeStats, label), shapeStats.GetLabels())</span></div>
</div>
<div class=""><br class="">
</div>
<div class=""><br class="">
</div>
<div class="">This uses advance concepts of multi-threading, closures, mapping, and thread pools. I think it is the integration of SimpleITK any Python at its bests!</div>
<div class=""><br class="">
</div>
<div class="">One tweak which could be made to this code is to create a RegionOfInterestImageFilter object, and explicitly set it’s number of threads to 1, so that it is not multi-threaded.</div>
<div class=""><br class="">
</div>
<div class="">A related not is the recently Oriented Bounding Box computation has been added to ITK’s LabelShape objects and filters, this is starting to get propagated into SimpleITK now. This can be used for a similar purpose but with a resample image filter
to change the orientation of the separate object.</div>
<div class=""><br class="">
</div>
<div class="">Enjoy!</div>
<div class="">Brad</div>
<div class=""><br class="">
<div>
<blockquote type="cite" class="">
<div class="">On May 22, 2017, at 5:59 AM, Jonas Teuwen <<a href="mailto:jonasteuwen@gmail.com" class="">jonasteuwen@gmail.com</a>> wrote:</div>
<br class="Apple-interchange-newline">
<div class="">
<div dir="ltr" class="">
<div class="">
<div class="">
<div class="">
<div class="">Dear all,<br class="">
<br class="">
</div>
Currently I have SimpleITK code to extract patches from a 3D medical image to train a neural network with. I do this with CropImageFilter and check if they are on the edge or not, and pad if necessary.<br class="">
<br class="">
</div>
Currently this is done offline, so speed is not really an issue, however, I would like to do this online now, so load the image and mask, and return the patches. If I want to extract many small patches, about 1000 out of a large image (~3000x3000x50 or so)
is there any reason why I would not use OpenMP instead of ITK's possibilities? I do not have a good understanding of the multithreading capabilities yet, so any pointers would be great.<br class="">
<br class="">
</div>
Best,<br class="">
</div>
Jonas Teuwen<br class="">
<div class="">
<div class=""><br class="">
</div>
</div>
</div>
_____________________________________<br class="">
Powered by <a href="http://www.kitware.com" class="">www.kitware.com</a><br class="">
<br class="">
Visit other Kitware open-source projects at<br class="">
<a href="http://www.kitware.com/opensource/opensource.html" class="">http://www.kitware.com/opensource/opensource.html</a><br class="">
<br class="">
Kitware offers ITK Training Courses, for more information visit:<br class="">
http://www.kitware.com/products/protraining.php<br class="">
<br class="">
Please keep messages on-topic and check the ITK FAQ at:<br class="">
http://www.itk.org/Wiki/ITK_FAQ<br class="">
<br class="">
Follow this link to subscribe/unsubscribe:<br class="">
http://public.kitware.com/mailman/listinfo/insight-users<br class="">
</div>
</blockquote>
</div>
<br class="">
</div>
</body>
</html>