Y EARLIER experiences with Konqueror go back to ~2002 when I tried it at work under Mandrake, around the early versions of KDE3 or later KDE2. Konqueror had many menu options and was daunting in some ways compared to Netscape and Mozilla. In KDE 3.1 Konqueror had acceptance problems among Web sites that were simply IE-centric or IE- and Netscape-centric. This was not a problem in Konqueror itself, but it made life a little harder for Konqueror users like myself. I only moved to Firefox some time in 2004 and it is still my Web browser of choice, having tested Chromium and some other browsers for a while (they lack plugins).

Anyway, under Fedora 14 I am attempting to use Konqueror exclusively and it’s generally a pleasant experience. After over a week of use I’ve only experienced two issues; one is when opening a PDF which Okular tried to embed within the Web page/rendering frame (this is easily solvable by opening the PDFs in an external application like the excellent Okular); the second issue is repeatable and reproducible crashes under WordPress’ media management menu. It’s a Web application-specific issue and debugging would be needed.

Workarounds are quite simple to find and the general experience working with Konqueror is finally quite pleasant (I tried Konqueror exclusively for about half a week in KDE 4.3 but eventually gave up). Speed is not great and there is room for improvement, but for general-purpose light usage Konqueror would fit most people’s needs. Some time later this month I will write about KDE 4.5 as a whole.

AGGING in the context of image acquisition involves getting magnetic signal by selectively sending charges to the tissue, whose atoms (usually just hydrogen is targeted by adjustment of frequencies) equipment can try to test for response in such a way that under normal conditions without noticeable change they would return a rectangular grid overlaid on top of the data. This enables better tracking of tissue motion that’s robust to spatially-similar atoms (whose returned signal is hard to discern visually). This post is a personal and informal quick survey of some resources which people may hopefully find helpful. It is not a detailed or comprehensive analysis.

Background

Tagging has many areas about or around it which ought to be explored. Back in 2003, an extension of the approach — one of complementary innovation in particular — was a goal yet to be accomplished although many extensions already exist. As Professor Leon Axel from the Department of Radiology at NYU School of Medicine (he is the inventor of tagging) put it in his paper “Tagged MRI-Based Studies of Cardiac Function” (2003), improvements in tagged MRI methods include optimisation in terms of speed and 3-D as well. To quote, “[s]ome ways in which we are seeking to improve tagged imaging include improved physiologic motion synchronization, faster imaging methods and 3D image acquisition.”

In case magnetic resonance cannot be properly applied for 3-D tagged images, other modalities can perhaps be considered at an early stage where data to work on is being sought and gradually collected starting with coarse image sequences (more on that later). However, it is tagging which probably yields the most valuable information, adding it to one of the most valuable imaging modalities. As Wikipedia explains it, Speckle Tracking Echocardiography, for example, “analyzes motion within an ultrasonic window by tracking intereference patterns and natural acoustic reflections.[1] These reflections, also described as ‘‘speckles’’, ‘‘markers’’, ‘‘patterns’’, ‘‘features’’, or ‘‘fingerprints’’ are tracked consecutively frame to frame and ultimately resolved into angle-independent two-dimensional (2D) and three-dimensional strain-based sequences (3D) [2][3][4] These sequences provide both quantitative and qualitative information regarding tissue deformation and motion.”

The connection to MRI is mentioned further down where it says: “The utilities of STE are increasingly recognized. Strain results derived from STE have been validated using sonomicrometry and tagged MRI and results correlate significantly with tissue Doppler–derived measurements.[7][8][9]”

Reference 8 is “Amundsen BH, Helle-Valle T, Edvardsen T, Torp H, Crosby J, Lyseggen E,et al. Noninvasive myocardial strain measurement by speckle tracking echocardiography: validation against sonomicrometry and tagged magnetic resonance imaging. J Am Coll Cardiol 2006;47:789-93″

Tagging seems to be explored a lot in NYU, Penn State University, and also Johns Hopkins University (there is group outside the United States which works on this area as well, but further reading will probably reveal many more such groups). N.F. Osman and J.L. Prince from Johns Hopkins University, for example, wrote about “Angle images for measuring heart motion from tagged MRI” (presented in the 1998 International Conference on Image Processing in Chicago, Illinois). The abstract says that their work “introduces a new image processing technique for rapid analysis and visualization of tagged cardiac magnetic resonance (MR) images. The method is based on the use of isolated spectral peaks in SPAMM-tagged magnetic resonance images. The authors call the phase of an image corresponding to just one of these peaks an angle image, and show that except for a phase-wrapping artifact, an angle image is linearly related to a component of the three-dimensional motion. Using one or more angle images, the authors show how to synthesize conventional tag lines, reconstruct displacement fields for small motions, calculate the optical flow between successive temporal images, and calculate two-dimensional strain. The authors demonstrate the performance of this approach on both real and simulated tagged MR images”

Ten years later, 4-D work (including temporal) was done by the group from NYU School of Medicine along with Dimitris N Metaxas and Zhen Qian [2] (from the Center for Computational Biomedicine Imaging and Modeling at Rutgers University). They published “A Segmentation and Tracking System for 4D Cardiac Tagged MR Images” (issue date of 2006, with current version from 2008). Their paper from EMBS ’06 (28th Annual International Conference of the IEEE) “present[s] a robust method for segmenting and tracking cardiac contours and tags in 4D cardiac MRI tagged images via spatio-temporal propagation. Our method is based on two main techniques: the Metamorphs segmentation for robust boundary estimation, and the tunable Gabor filter bank for tagging lines enhancement, removal and myocardium tracking.”

The Institute of Biomedical Engineeering at Bogazici University (Istanbul, Turkey) has also published [3] “Towards rapid screening of tagged MR images of the heart” and the abstract reads: “The final aim of this work is to perform rapid classification of tagged cardiac MR images as normal and abnormal. In the proposed technique, images are first analyzed using harmonic phase analysis and synthetic tags are computed over the myocardium. Cubic curves are fitted to these tags and curve parameters are compared at various regions of the myocardium. In this initial study, the ratios of curve parameters between normal and diseased hearts, such as dilated cardiomyopathy (DCM) and heart with infarcted regions, are evaluated. If the initial segmentation problems are solved, this method could be a very fast and automatic screening tool for identifying diseased locations in tagged MRI.”

Background to My Work

A while ago I began implementing an approach where I explore new methods of anatomical structures extraction based on tagging. After spending a long time trying to get my hands on some data with tagging in it (low-resolution videos is the best I have found on the Web so far [1, 2, 3]) I managed to find MRI cardiac data which the people from New York can share with us. Getting data with tagging has proven tricky unless there is direct access to the right people and I’m grateful to receive some good data as I’m eager to work on extending and complementing the work which is Axel’s breakthrough. Doing so without the required data would be hard. One possibility for working with such data is to locally work on sythesising or emulating a set of tagged image using specific software which does this quite nicely. It may be good if we need to test programs where the ground truth solution is known. Otherwise, approaching the group from New York was a reasonable option to be exploring and with enough data, both real and synthetic data can be used, one for actual work and another for validation of the method.

Why Shuffle Distance/Difference

In a later short paper I’ll explain the approach of encoding the image in terms of bytes (8 bits) or blocks of 64 bits that can be handled by particular CPUs more efficiently and thus have an image stored and processed (even in 3-D) with little burden on the hardware, yielding faster results for real-time tracking of the tags. There is an existing implementation left from my work on brain images where this is done in a vectorised fashion and works quite fast in Octave (bar JIT) or MATLAB. Whether tagging in 3-D is available at all remains to be seen. That is a subject for another day.

References:

[1] N.F. Osman, J.L. Prince, “Angle images for measuring heart motion from tagged MRI,” International Conference on Image Processing, vol. 1, pp.704, 1998.

[2] D. N. Metaxas, L. Axel, Z. Qian, and X. Huang, “A Segmentation and Tracking System for 4D Cardiac Tagged MR Images,” Engineering in Medicine and Biology Society, pp. 1541–1544, 2006.

[3] D. Goksel, M. Ozkan, and C. Ozturk, “Towards rapid screening of tagged MR images of the heart,” Engineering in Medicine and Biology Society, vol. 1, pp. 156–159, 2001.

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Summary: Another fun show includes our guest Gordon Sinclair, who helps us learn about the value of Mint and discusses a plethora of other topics

HIS is our eighth episode. Gordon, Tim, and Roy speak about a range of issues with special focus on Linux Mint upon its new release, called/dubbed “Julia”. While not talking about Mint we also go through the differences between Windows and GNU/Linux in general. At the end we discuss some of the latest bad news that Windows Phone 7 needs to cope with (storage problems). Tim’s site, OpenBytes, will soon share some links about the topics we cover. Gordon’s good site can be used to keep track of his work, including some projects he tells us about in advance (it is at the very end of the show).

Today’s show ends with our theme song from Tom Smith. We hope you will join us for future shows and spread the word if you enjoy this show. Also consider subscribing to the show via the RSS feed. If you have an Identi.ca account, consider subscribing to TechBytes in order to keep up to date. We have begun listing past shows at the bottom of each post, based on listeners’ feedback that suggested this.

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Summary: A daily news roundup with special focus on an easy-to-debunk GNU/Linux ‘article’ from The Economist

HIS is the seventh episode, which Tim and Roy keep short to obey requests from regular listeners of the show. Our leading story today is a fun FUD piece from The Economist, which is talked about for the first 10 minutes or so. Tim’s site, OpenBytes, will share some links about that.

Today we play no special song and instead revert back to our default one from Tom Smith. We hope you will join us for next week’s shows, which will be more packed with stories.

As always, if you enjoy this show, please consider recommending it to others and consider subscribing to the show via the RSS feed. If you have an Identi.ca account, consider subscribing to TechBytes in order to keep up to date.

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Keywords: Open Access; Free software; Cardiac cine-MRI; Brain; Segmentation; Tagging; Cardiac deformation analysis

Overview

his informal post presents a quick survey of what’s available for one to find when it comes to heart tagging downloads (without having to go through radiologists and all sorts of burdensome forms). It is a problem I’ve been tackling recently and I would like to share my findings to make life easier for other scientists who find themselves in the same situation.

Some Background Information

WEEK OR SO ago I decided to share information about the availability of datasets for researchers. When faced with the problem of looking for, say, ‘”tagged MR” images heart download dicom’ (and a lot of searching around this phrase) I was surprised to find that almost nobody publicly shared or made discoverable a dataset one can use for research purposes. In order to simplify the task for others who find themselves in a similar situation, several days ago I wrote about my intentions to make a sort of summary [1, 2].

As a bit of background, our original plan was to write and implement special protocols with engineers at the MRI scanner, as part of the research effort by which special types of data are obtained for a novel approach to be tested. This is explained in a paper I’ll put up in the site pretty soon.

At the moment, due to particular constraints, we are working on analysis of sequences of tagged data. This obviously requires not just MR images of the heart but also sequences and these, preferably sequences that must have particular types of tags which a radiologist would use. Data can be acquired/sliced from different angles and obtained from any subject/patient at the hospital^*, but for this particular approach that we test (to be covered in a separate post) this is rather irrelevant as we want it to be applicable regardless of factors like angles, subjects, and potentially their atrophies.

Resources

SourceForge hosts quite a few MRI-related software projects which are free/libre and thus of value to MRI-based research (our methods and data should be made freely accessible for independent validation). One of these projects is the cardiac MR toolbox for Matlab, which may also be fully compatible with Octave (free/libre software). “The cardiac MR (CMR) toolbox for Matlab,” explains the official Web page, “provides tools for image registration, perfusion analysis, segmentation, and image reconstruction from sparsely sampled data.” Here is the alternative project homepage. It states:

This is the Cardiac MR toolbox for Matlab project (“cmr-toolbox”)

This project was registered on SourceForge.net on Mar 29, 2010, and is described by the project team as follows:
The cardiac MR (CMR) toolbox for Matlab provides tools for image registration, perfusion analysis, segmentation, and image reconstruction from sparsely sampled data.”

For brain MRI there is the RESCUE brain MRI segmentation project. It is not yet available, but it soon will be. Its author states: “RESCUE will be made available after publication of the PhD thesis of James Withers (Uni of Edinburgh, UK). The first version of the package will initially include super-resolution, thin structure detection, and partial volume estimation components.”

Of course, one can get brain datasets from the rather famous BrainWeb (more here) and some more data resides in my site, including a sample set of images and some DICOM-formatted data of my own brain (acquired at Hope Hospital for a colleague’s experiment back in 2005).

Moving on to the heart, there is a cardiac MRI dataset which is not terribly useful because almost everything is encoded and stored in MATLAB format and may therefore require some loaders that are proprietary (Octave does not cope so well with those).

There is another project called inTag and this Web pageoffers a a look at what’s done there. Another page offers a look at how it’s used. It is “a software to calculate, display and analyze myocardial strains and intra-myocardial mechanics from cardiac MR images with a tagging pattern.”

The dependencies on proprietary software are unfortunate though. As the page puts it: “After a preliminary prototyping step in Matlab ®, InTag is now available as a plugin in OsiriX, the advanced open-source image processing software. It benefits of all its unique capabilities for navigation, visualisation of multimodality and multidimensional images, and data management.”

This requires OsiriX, which is Free/open source software, but only for Macs, which is not terribly useful then. Here is some tagging from this software package called inTag. It’s just a group of some very low-resolution images in DICOM format (small and not so useful at all).

Another dataset which I find odd (not because it’s made available just in very low resolution but because there is something odd in orientation) comes from New Zealand. Images are said to be available for download, but they are all encoded as AVI-formatted slanted videos and also compressed. The only one set with tagging data is not too helpful, either. The page states that “The Auckland MRI Research group has agreed to make freely available 256×256 JPEG images and image orientation information for download. In addition the Auckland MRI Research group has also agreed to make freely available the cines in AVI format”. What’s listed in the page as an overview is as follows:

All 119 T1-weighted jpeg images
akld-mrirg-atlas-jpegs.zip (4.33MB)
12 Long axis trueFisp avi movies
akld-mrirg-cines-truefisp-long.zip (21.76MB)
1-15 Short axis trueFisp avi movies
akld-mrirg-cines-truefisp-short-a.zip (25.32MB)
16-30 Short axis trueFisp avi movies
akld-mrirg-cines-truefisp-short-b.zip (28.61MB)
3 Aorta and 1 RVOT trueFisp avi movies
akld-mrirg-cines-truefisp-aorta-rvot.zip (7.42MB)
11 Long axis and 15 Short axis tagged avi movies
akld-mrirg-cines-tagging.zip (26.46MB)
Aorta(2) / Right(2) and Left(2) Pulmonary arteries(4) phase contrast avi
movies akld-mrirg-cines-phasecontrast.zip (10.34MB)

Those sets are not tagged except akld-mrirg-cines-tagging.zip. There is also no data from the Cincinnati Children’s Hospital Medical Center, which shows up among many search results. Search for data has proven to be quite fruitless, generally speaking.

Eventually I used data which I acquired from someone’s thesis frame by frame, only to be seen as a temporary solution until data comes from a group that keeps it for internal use. The conclusion is that the Web is generally a poor resource for such data, especially if tagging is a requirement. If someone knows of an exception, please comment below.

Some References

On this fruitless pursuit for data the following references were seen as potentially relevant (publication names mostly omitted as it’s easy to search by title).

DN Metaxas, “A Segmentation and Tracking System for 4D Cardiac Tagged MR Images,” 2008.

L Axel, “Tagged MRI-Based Studies of Cardiac Function,” Computerized Medical Imaging and Graphics, Volume 29, Issue 8, December 2005, Pages 607-616, 2003.

D Goksel, “Towards rapid screening of tagged MR images of the heart,” 2002.

NF Osman, “Angle Images for Measuring Heart Motion from Tagged MRI.”

L Axel, “An Integrated Program for 2-D and 3-D Analysis of Heart Wall…,” 2002.

Y. Chenounea, “Segmentation of cardiac cine-MR images and myocardial deformation assessment using level set methods,” 2005.

(Abstract: “In this paper, we present an original method to assess the deformations of the left ventricular myocardium on cardiac cine-MRI. First, a segmentation process, based on a level set method is directly applied on a 2D+t dataset to detect endocardial contours. Second, the successive segmented contours are matched using a procedure of global alignment, followed by a morphing process based on a level set approach. Finally, local measurements of myocardial deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results to the measurements achieved on the same patients by an expert using the semi-automated HARP reference method on tagged MR images.)
____
^* Some are too blurry and others paint areas with blood presence black, which help isolate the boundaries of important structures for subsequent analysis.

few days ago I started working with Fedora 14. So far, so good, at least as far as the desktop machine goes (a laptop is another story and Kubuntu runs fine on another desktop). Something has just happened in Fedora which never happened to me before. Kate (an editor) got stuck and its memory (RAM) consumption went up through the roof to over 1.5 GB, so obviously it froze the system for a while. The process needed to be forcibly killed.

Now, it’s not entirely clear what happened there (maybe a program bug), but this is unusual and it looks bad for Fedora or for KDE (or the combination in Fedora 14 KDE spin). What did happen is that SELinux came up with an error implying that it stood in Kate’s way and maybe it’s partly responsible for this type of behaviour. It yielded the following error, implying that it was trying to help when in fact it seemed like it only stood in the way.

Summary:

SELinux is preventing /usr/bin/kate (deleted) “mmap_zero” access on <Unknown>.

Detailed Description:

SELinux denied access requested by kate. The current boolean settings do not
allow this access. If you have not setup kate to require this access this may
signal an intrusion attempt. If you do intend this access you need to change the
booleans on this system to allow the access.

Allowing Access:

Confined processes can be configured to run requiring different access, SELinux
provides booleans to allow you to turn on/off access as needed. The boolean
mmap_low_allowed is set incorrectly.
Boolean Description:
Control the ability to mmap a low area of the address space, as configured by
/proc/sys/kernel/mmap_min_addr.

Fix Command:

# setsebool -P mmap_low_allowed 1

Additional Information:

Source Context unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1
023
Target Context unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1
023
Target Objects None [ memprotect ]
Source kate
Source Path /usr/bin/kate (deleted)
Port &ltUnknown>
Host blueberry
Source RPM Packages
Target RPM Packages
Policy RPM selinux-policy-3.9.7-3.fc14
Selinux Enabled True
Policy Type targeted
Enforcing Mode Enforcing
Plugin Name catchall_boolean
Host Name blueberry
Platform Linux blueberry 2.6.35.6-45.fc14.i686 #1 SMP Mon
Oct 18 23:56:17 UTC 2010 i686 i686
Alert Count 112
First Seen Sun 14 Nov 2010 09:35:01 AM GMT
Last Seen Sun 14 Nov 2010 09:35:17 AM GMT
Local ID 4d9759c9-e672-475d-bf61-151d1688909a
Line Numbers

Raw Audit Messages

node=blueberry type=AVC msg=audit(1289727317.378:856): avc: denied { mmap_zero } for pid=1880 comm=”kate” scontext=unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023 tcontext=unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023 tclass=memprotect

node=blueberry type=SYSCALL msg=audit(1289727317.378:856): arch=40000003 syscall=192 success=no exit=-13 a0=0 a1=100000 a2=0 a3=4022 items=0 ppid=1629 pid=1880 auid=500 uid=500 gid=500 euid=500 suid=500 fsuid=500 egid=500 sgid=500 fsgid=500 tty=(none) ses=1 comm=”kate” exe=2F7573722F62696E2F6B617465202864656C6574656429 subj=unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023 key=(null)

For years I’ve been working with no data loss, but this time I had to revert back to a previously-saved version of a document I worked on and then rewrite bits of it. Perhaps I had enough confidence in the system to only hit save (CTRL+S) once in a very long time. This experience has taught me to save my work more often but more importantly it showed that Fedora can act rather bizarrely where Kubuntu never did. As a result of this behaviour I was unable to save my work. SELinux implies there was an “attack” on the system, but obviously there was not.

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Summary: A weekly roundup with special focus on hands-on experience and impressions of the latest major release of GNU/Linux, namely Fedora 14

HIS is the sixth episode, which has just been recorded by Tim and Roy. This was done right after today’s testing of Fedora and Fusion 14. I installed it permanently on 2 boxes, whereas Tim tried Fusion on his side and, as usual, his site OpenBytes has some show notes. As we’ve both had a chance to test it on some machines, we may also post detailed reviews soon (c.f. [cref 41364 our first show], which was a Fedora 14 special that covered Fusion too).

To summarise my experience in textual form, it was a KDE-only experience and an especially wonderful one. Having just installed Fedora 14 on another box and encountered very few difficulties (ClaudioM and other people who spoke back to me were generally happy with it as well, only with minor pet peeves). I spent many hours on it, getting a feel for what’s installed, what works, and what is harder to use. Among the installations, the first, on a desktop, went smoothly, but the second, a notebook, had the same issue as Mandriva had with it (built-in microphone not detected, so external one needed). There is a lot to be said about the startup speed and about Plasma, which has nonetheless given me a hard time today. Plasma-desktop in KDE (4.5) is very pleasant and it provides a good-looking desktop and brilliant experience. Unfortunately it decided to repeatedly crash on the laptop and it’s possibly simple to resolve (will retry tomorrow).

As time goes on, TechBytes manages to become more focused, concise, and also incorporate a logical structure which makes it easier to follow. We also intend to end every show with a song from now on. This show closes with “On My Kees” from Aqualung (freely obtainable via SXSW 2009 Showcasing Artists).

If you wish to be on the show or know someone who ought to be on the show, please let us know. Marti spoke with us for a long time today, but we are trying to sort out recording difficulties which will hopefully be overcome soon. We are eager to have him on a future show.

As always, if you enjoy this show, please consider recommending it to others and consider subscribing to the show via the RSS feed. If you have an Identi.ca account, consider subscribing to TechBytes in order to keep up to date.

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