hown here are two images derived from experiments out of which there are also videos. The set of cardiac images contains 340 images, divided into 17 groups of 20 images belonging to each. A group of 20 consecutive images represents one slice imaged throughout one cardiac cycle. This means that from the 2^nd and 4^th slides — images 21 and 61 respectively for example — the signal is approximately correspondent and thus can be compared. A series of experiments was performed in turn, dealing with each slice in isolation and learning how our algorithm copes with the complicated task of tracking the heart’s walls without a priori knowledge such as a model of the heart, for example (a model whose parameter values can be optimised over, for a good fit to be eventually found). We are interested in the rotation of the heart at the different vertical levels, particularly because we expect to see clockwise and counterclockwise movements throughout the cycle, depending on the slice (the heart squeezes blood by moving in different — almost opposite — directions).

The results are encouraging. Leaving aside slices that hardly contain any signal from the heart because they are at the top and bottom edges, it is quite consistently found that there is a clockwise rotation at the centre, detected by averaging the direction of the move of many salient points. In the middle slices in particular (those in which the heart gives more signal owing to greater overall area), the curves are entirely, or at least almost entirely, monotonic, which means that at each iteration the clockwise rotation continues. This can help show some otherwise-hidden information, but more datasets and rigorous testing on synthetic data for validation may be required as well.

QtOctave on Kubuntu with a
MATLAB window imported from Fedora over SSH

or the sake of cross-application/framework compatibility, one occasionally needs to alter code until it works everywhere, without the need to keep two (or more) separate codebases. This situation is far from ideal, but then again, not everything works like Java. When colleagues use a different platform and occasionally prefer proprietary software it is only fair to do some extra work catering for it.

In a matter of days or maybe a few weeks I will have some new code ready for release. I had already released this before it was ready for stable usage, partly because I had not set up a proper repository, so each release of code become a manual process. This may change soon.

In the early part of the day I ensured my programs work in both MATLAB and Octave. It was not as trivial as I had expected because there is certain functionality in Octave which MATLAB simply does not support. There are notes that I took to summarise and thus simplify this task in the future. The code now works in the latest MATLAB and also in Octave, with very minor differences between these two. The same set of files can be used for both, interchangeably.

Over the course of my work I have organised the data, documentation, experimental results, and code. All of these can be neatly packaged to provide the tools necessary for others to extend the program and use it to run more experiments. Following a very thorough survey of programs that are already available around the Web, it does not appear as though opportunities to reuse code were missed. At the moment, the program has an interface function with clearly-defined inputs and its output — in the form of images and video — is sent to a directory of choice at the end.

What would be nice to attempt next is implementation of other methods that assess similarity between regions, as means of selecting points more accurately. Making the placement of points diffeomorphic so that nothing gets folded or torn between the connecting curves that make up the contours would be essential too, especially for visualisation and 3-D reconstruction for example. At the moment it is possible to take point positions at each slice and each of the 20 iterations contained for that slice and then produce — using polygons — a sort of 3-D model of the heart. This, however, would require results to be of higher precision too.

uring the holidays I decided to see what else is out there which is already free/libre software like my own work, which thus can be merged for comparative purposes. It would be valuable to have applied to my work some comparison to existing tracking algorithms which deal with cardiac images. A decade-old paper from Osman et al. covers the very popular HARP and states in its abstract that it offers an “image processing technique for rapid analysis of tagged cardiac magnetic resonance image sequences.[...] Results from the new method are shown to compare very well with a previously validated tracking algorithm.” It’s not easy to gain access even to code samples of complete frameworks that facilitate benchmarking, so the search ascended to SourceForge. I uploaded some projects of mine to SourceForge about 8.5 years ago and hoped that others would do the same. A search in SourceForge for “cardiac” yields about a dozen results (at the time of writing), but there are empty entries in the code repositories where there ought to be complete projects. The Cardiac MR toolbox for Matlab, for instance, is an empty project:

[roy@blueberry cmr-toolbox]$ svn co
https://cmr-toolbox.svn.sourceforge.net/svnroot/cmr-toolbox cmr-toolbox
Checked out revision 0.
[roy@blueberry cmr-toolbox]$ ls
cmr-toolbox
[roy@blueberry cmr-toolbox]$ cd cmr-toolbox/
[roy@blueberry cmr-toolbox]$ ls
[roy@blueberry cmr-toolbox]$

The same goes for Neonatal Rat Cardiac Action Potential, but the Evaluation of Cardiac MR Segmentation project (all of them written for MATLAB but ought to be compatible with Octave) contains some LGPL-licensed code. Repository access (SVN):

svn co https://cardiac-mr.svn.sourceforge.net/svnroot/cardiac-mr cardiac-mr

Looking at MATLAB Central for some more existing code I find an old BSD-licensed function but almost nothing else when searching for “Cardiac”. Since the literature review phase and the subsequent finding of some data [1, 2, 3] there has been almost no room for code reuse, so I had to code everything from scratch. I will soon publish the code (GPLv3-licensed), but in a more scientific society more code would have already been out there for others to collaborate and build upon the work of others.

aving encountered problems with Octave in Fedora 14, I decided to explore scilab, which I wanted to try about a week ago anyway (and canceled the process after being warned that it was not as complete as octave, at least not for my needs). Fedora does not appear to have scilab in its repositories (Ubuntu on the other hand does have it). A yum and kpackagekit search around “scilab” yields nothing, so I went to the official scilab Web site and downloaded the latest package from that nice Web site, then uncompressed it. This was not the end of it as far as Fedora was concerned because, due to it not being available in the repositories, dependencies could not be resolved, so I needed to also install java manually, then figure out that SELinux was standing in my way. This is the type of thing which would deter new users and as much as I would love to endorse Fedora 14, it is experiences like this which leads me to saying that Kubuntu is still a better choice. Here is a self-explanatory story:

[roy@blueberry scilab-5.2.2]$ ls
ACKNOWLEDGEMENTS  CHANGES_3.X    CHANGES_5.2.X  lib            RELEASE_NOTES_5.0.X  thirdparty
bin               CHANGES_4.X    COPYING        license.txt    RELEASE_NOTES_5.1.X
CHANGES           CHANGES_5.0.X  COPYING-FR     README_Unix    RELEASE_NOTES_5.2.X
CHANGES_2.X       CHANGES_5.1.X  include        RELEASE_NOTES  share
[roy@blueberry scilab-5.2.2]$ cd bin/
[roy@blueberry bin]$ ls
intersci  modelicac  scilab  scilab-adv-cli  scilab-bin  scilab-cli  scilab-cli-bin
[roy@blueberry bin]$ ./scilab

Could not load JVM dynamic library (libjava).
Error: libjvm.so: cannot enable executable stack as shared object requires: Permission denied
If you are using a binary version of Scilab, please report a bug http://bugzilla.scilab.org/.
If you are using a self-built version of Scilab, update the script bin/scilab to provide the path to the JVM.
The problem might be related to SELinux. Try to deactivate it.

Scilab cannot open JVM library.
[roy@blueberry bin]$ su
Password: 
[root@blueberry bin]# yum install libjava
Loaded plugins: langpacks, presto, refresh-packagekit
Adding en_US to language list
Setting up Install Process
No package libjava available.
Error: Nothing to do
[root@blueberry bin]# yum install java
Loaded plugins: langpacks, presto, refresh-packagekit
Adding en_US to language list
Setting up Install Process
Resolving Dependencies
--> Running transaction check
---> Package java-1.6.0-openjdk.i686 1:1.6.0.0-44.1.9.1.fc14 set to be installed
--> Processing Dependency: jpackage-utils >= 1.7.3-1jpp.2 for package: 1:java-1.6.0-openjdk-1.6.0.0-44.1.9.1.fc14.i686
--> Processing Dependency: rhino for package: 1:java-1.6.0-openjdk-1.6.0.0-44.1.9.1.fc14.i686
--> Processing Dependency: tzdata-java for package: 1:java-1.6.0-openjdk-1.6.0.0-44.1.9.1.fc14.i686
--> Running transaction check
---> Package jpackage-utils.noarch 0:1.7.5-3.11.fc14 set to be installed
---> Package rhino.noarch 0:1.7-0.7.r2.fc12 set to be installed
--> Processing Dependency: jline for package: rhino-1.7-0.7.r2.fc12.noarch
---> Package tzdata-java.noarch 0:2010o-1.fc14 set to be installed
--> Running transaction check
---> Package jline.noarch 0:0.9.94-0.6.fc14 set to be installed
--> Finished Dependency Resolution

Dependencies Resolved

=======================================================================================================
 Package                     Arch            Version                            Repository        Size
=======================================================================================================
Installing:
 java-1.6.0-openjdk          i686            1:1.6.0.0-44.1.9.1.fc14            fedora            27 M
Installing for dependencies:
 jline                       noarch          0.9.94-0.6.fc14                    fedora            88 k
 jpackage-utils              noarch          1.7.5-3.11.fc14                    fedora            60 k
 rhino                       noarch          1.7-0.7.r2.fc12                    fedora           775 k
 tzdata-java                 noarch          2010o-1.fc14                       updates          151 k

Transaction Summary
=======================================================================================================
Install       5 Package(s)

Total download size: 28 M
Installed size: 84 M
Is this ok [y/N]: y
Downloading Packages:
Setting up and reading Presto delta metadata
updates/prestodelta                                                             | 248 kB     00:00     
Processing delta metadata
Package(s) data still to download: 28 M
(1/5): java-1.6.0-openjdk-1.6.0.0-44.1.9.1.fc14.i686.rpm                        |  27 MB     00:10     
(2/5): jline-0.9.94-0.6.fc14.noarch.rpm                                         |  88 kB     00:00     
(3/5): jpackage-utils-1.7.5-3.11.fc14.noarch.rpm                                |  60 kB     00:00     
(4/5): rhino-1.7-0.7.r2.fc12.noarch.rpm                                         | 775 kB     00:00     
(5/5): tzdata-java-2010o-1.fc14.noarch.rpm                                      | 151 kB     00:00     
-------------------------------------------------------------------------------------------------------
Total                                                                  2.2 MB/s |  28 MB     00:12     
Running rpm_check_debug
Running Transaction Test
Transaction Test Succeeded
Running Transaction
  Installing     : jpackage-utils-1.7.5-3.11.fc14.noarch                                           1/5 
  Installing     : jline-0.9.94-0.6.fc14.noarch                                                    2/5 
  Installing     : rhino-1.7-0.7.r2.fc12.noarch                                                    3/5 
  Installing     : tzdata-java-2010o-1.fc14.noarch                                                 4/5 
  Installing     : 1:java-1.6.0-openjdk-1.6.0.0-44.1.9.1.fc14.i686                                 5/5 

Installed:
  java-1.6.0-openjdk.i686 1:1.6.0.0-44.1.9.1.fc14                                                      

Dependency Installed:
  jline.noarch 0:0.9.94-0.6.fc14                jpackage-utils.noarch 0:1.7.5-3.11.fc14               
  rhino.noarch 0:1.7-0.7.r2.fc12                tzdata-java.noarch 0:2010o-1.fc14                     

Complete!
[root@blueberry bin]# ./scilab

Could not load JVM dynamic library (libjava).
Error: libjvm.so: cannot enable executable stack as shared object requires: Permission denied
If you are using a binary version of Scilab, please report a bug http://bugzilla.scilab.org/.
If you are using a self-built version of Scilab, update the script bin/scilab to provide the path to the JVM.
The problem might be related to SELinux. Try to deactivate it.

Scilab cannot open JVM library.
[root@blueberry bin]# killall selinux
selinux: no process found
[root@blueberry bin]# ./scilab

Could not load JVM dynamic library (libjava).
Error: libjvm.so: cannot enable executable stack as shared object requires: Permission denied
If you are using a binary version of Scilab, please report a bug http://bugzilla.scilab.org/.
If you are using a self-built version of Scilab, update the script bin/scilab to provide the path to the JVM.
The problem might be related to SELinux. Try to deactivate it.

Scilab cannot open JVM library.
[root@blueberry bin]# ./scilab

This worked the second time only because I made SELinux more permissive, but this could have many users give up. Here is what I then got:

As expected, there is no support for some fairly basic functions in scilab, which is not a complete octave replacement.

-->imshow('in')
             !--error 4 
Undefined variable: imshow

 
 
-->imread('in')
             !--error 4 
Undefined variable: imread

I do not want to install MATLAB or Fedora (although we do have an academic licence), but experiences with Fedora so far may drive me towards installing proprietary software or simply working from another box which happens to be better equipped and work perfectly well with Octave. That box runs Kubuntu.

HIS DRAFT-LEVEL OR DRAFT-QUALITY POST is not a detailed literature review but only an attempt to group together papers of interest and highlight those which are potentially relevant to in vivo studies of the heart, such as studies that distinguish between a healthy heart and a diseased one based on its motion. In this work, the goal is to study the registration and/or analysis of heart images and how one can overcome the 3 types of movement which occur at a rapid rate with less than one second per cycle, where the heart twists and shrinks (changes in volume), thus leading to ambiguity and confusion. The muscle tissue inside the heart and outside the heart is positioned in such a way that fibre sticks at a roughly 60-degree angle perpendicular to the heart, with the outside being at odds wrt to the angle that’s seen on the inside. Things change when blood is being pumped.

My initial goal revolves around 3-D heart reconstruction, tracing/tracking cardiac activity, attempting an approach of an isolated cube with occlusion to track one position of the heart amid movement (if that fails, there is another simpler shape analysis approach from around 1990).

I have been shifting focus from my background in analysis of brain MRI (and to a limited extent exploration of face images for recognition of sets and statistical analysis of these). Cardiac 3-D is a subject which may require an introduction to the heart and its dynamics in particular.

The Wikipedia article which focuses mostly on the human heart clarifies that the term cardiac (as in cardiology) means “related to the heart” and comes from the Greek kardia, which can be almost be substituted to mean “heart”. Some useful pages from the University of Minnesota are worth a look. Here is a nice interactive map with which to study the anatomy of the heart but not its operation. Cardiac anatomy can be learned from it. Lastly, the Atlas of Human Cardiac Anatomy allows viewing the heart as it pumps blood. It is animated. Here is static photo of interest.

The unfortunate thing is that I remain dependent on MATLAB, which is the only proprietary piece of software (working properly on GNU/Linux though) I remains stuck with while doing my research, partly for collaboration purposes, which is ironic when the underlying framework is all secret and from a company that funds the BSA. It’s adverse to collaboration (I was once ranked first in the world for my MATLAB contributions in MATLAB Central and was offered to write a book when approached by MathWorks, which later tried to hire me). Anyway, digressing a bit, I will be still working on DICOM datasets, just as I was doing before.

Recent papers worth considering are [1] from Isola et al., who use an NRR approach similar to the one I practiced when handling MRI images of the human brain, where motion does not exist (or barely exists under normal conditions). It is applied to CT-acquired images and not to MRI though. The abstract sums up the purpose as follows: “Cardiac computed tomography is a rapidly emerging technique for noninvasive diagnosis of cardiovascular diseases. Nevertheless, the cardiac motion continues to be a limiting factor. Electrocardiogram-gated cardiac computed tomography reconstruction methods yield excellent results, but these are limited in their temporal resolution due to the mechanical movement of the gantry, and lead to residual motion blurring artifacts. If the motion of the cardiac region of interest is determined, motion compensated gated reconstructions can be applied to reduce motion artifacts. In this paper it is shown that elastic image registration methods can be an accurate solution to determine the cardiac motion.”

Another paper [2] which has only just been published looks at three-dimensional phase-contrast MRI and results included an experiment over the cardiac phase. In an attempt to find a comprehensive review of something which better fits my background (it involved a great deal of shape and intensity models) I came across last year’s review of shape models for 3-D image segmentation [3]. In efforts to identify a cardiac literature survey or background about the heart (be it a simple article or a literature survey), I found a paper from Zhuang et al. [4] about cardiac MRI for segmentation of the heart without human intervention. It does not quite deal with the problem of motion and real-time or offline tracking of parts of the heart (4-D), though. Motion caused by respiration is studied in [5] and it is relevant to the subject of tracking and its associated perils. There are many papers about tracking in all sorts of contexts and half a year ago there was a speckle-tracking echocardiographic study into myocardial deformation from the University of Hong Kong [6]. Having looked for material on in vivo tagging, I pinned down an article from 2003 [7] on “in vivo assessment of regional myocardial work in normal canine hearts using 3D tagged MRI.”

Other authors, having studies myocardial strains over a decade earlier [7], more recently looked at what they described as a “non-invasive method for assessing regional myocardial” [8] (in 2003). Cardiac tagging was done in Johns Hopkins University last year; namely, it was myocardial tissue tagging [9] with cardiovascular magnetic resonance (CMR). More on CMR tagging (from 2008) is to be found in [10] where mouse heart is studied. A paper from Wei et al. also considered CMR tagging by experimenting on mice [11]. Methods involved “[i]n vivo myocardial function was evaluated by 3D CMR tagging in mdx mice.”

The material on CMR tagging may be of high relevance and belonging to such a literature review would be [12], which “introduce[s] a standardized method for calculation of left ventricular torsion by CMR tagging and [determining] the accuracy of torsion analysis in regions using an analytical model.” Delling et al. [13] look at CMR and explain: “We sought to assess the correlation between mitral valve characteristics and severity of mitral regurgitation (MR) in subjects with mitral valve prolapse (MVP) undergoing cardiac magnetic resonance (CMR) imaging.”

In a very recent article warning about T2-weighted CMR, a detailed explanation is given which warns that, among other things, “[i]nconsistencies also exist in the clinical literature, and we still await multicenter validation of robustness, reproducibility, and additive clinical value.” This is irrelevant to the subject at hand, but it is also exceptionally recent. This was published by Nature and the headline was somewhat alarmist: “Molecular imaging: T2-weighted CMR of the area at risk—a risky business?”

Some less relevant papers on the subject may include [14]-[15] on CMR tagging. The problem of heart tracking or tracing of parts of the heart is a complicated one and a particular group has proposed “a novel dynamic model, based on the equation of dynamics for elastic materials and on Fourier filtering.”[16]

To some groups, robotic “intervention on the beating heart” is said to be a worthy route of exploration as well [17]. This one study on pig hearts [18] — like [6] — considers speckle-tracking.

Going through some of the latest material at jcmr-online.com (which is Open Access for the most part), one can also perform paper search around “cardiac tagging”, “mri tagging” and “heart mri tagging”. This yields not so many results. There’s a highly cited paper from approximately 20 years ago titled “Cardiac Tagging with Breath-Hold Cine MRI” (Open Access). If one is looking for an article which is/contains an overview of existing strands of work, there’s work to be done, but introduction sections may often help. There is a lot about HARP, including a paper from last year [19]. It is about a method which avoid the time-consuming post-processing associated with MRI images that were tagged.

Lastly, Cardiac Imaging has this new paper from 2010, which it makes viewable as HTML, not just to subscribers to the literature [20].

It is possible that I will make some posts on this subject in the future. My other two scientific blogs are in need of a makeover as they have not been updated for years. As stated at the start, this post is informal and part of an ongoing exploration of existing work in my research area.

References:

[1] “Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac CT reconstruction.”
Author(s): Isola, Alfonso A, Grass, Michael, Niessen, Wiro J
Source: Med Phys Volume: 37 Issue: 3 Pages: 1093-109 Published: 2010

[2] Title: “In vivo hemodynamic analysis of intracranial aneurysms obtained by magnetic resonance fluid dynamics (MRFD) based on time-resolved three-dimensional phase-contrast MRI.”
Author(s): Isoda, Haruo; Ohkura, Yasuhide; Kosugi, Takashi, et al.
Source: Neuroradiology Volume: 52 Issue: 10 Pages: 921-8 Published: 2010 Oct

[3] “Statistical shape models for 3D medical image segmentation: A review”
Author(s): Heimann, T; Meinzer, HP
Source: MEDICAL IMAGE ANALYSIS Volume: 13 Issue: 4 Pages: 543-563 Published: 2009

[4] Title: “A registration-based propagation framework for automatic whole heart segmentation of cardiac MRI.”
Author(s): Zhuang, Xiahai, Rhode, Kawal S, Razavi, Reza S, et al.
Source: IEEE Trans Med Imaging Volume: 29 Issue: 9 Pages: 1612-25 Published: 2010 (EPubDate 2010 08)

[5] “Respiratory motion correction in gated cardiac SPECT using quaternion-based, rigid-body registration.”
Author(s): Parker, Jason G, Mair, Bernard A, Gilland, David R
Source: Med Phys Volume: 36 Issue: 10 Pages: 4742-54 Published: 2009

[6] Myocardial deformation in patients with Beta-thalassemia major: a speckle tracking echocardiographic study.
Author(s): Cheung, Yiu-fai; Liang, Xue-cun; Chan, Godfrey Chi-fung; Wong, Sophia Jessica; Ha, Shau-yin
Source: Echocardiography Volume: 27 Issue: 3 Pages: 253-9 Published: 2010 Mar

[7] “Distribution of myocardial strains: an MRI study.”
Author(s): Azhari, H; Weiss, J L; Shapiro, E P
Source: Adv Exp Med Biol Volume: 382 Pages: 319-28 Published: 1995

[8] “Rapid MR imaging by sensitivity profile indexing and deconvolution reconstruction (SPID).”
Author(s): Azhari, Haim; Sodickson, Daniel K; Edelman, Robert R
Source: Magn Reson Imaging Volume: 21 Issue: 6 Pages: 575-84 Published: 2003 Jul

[9] “Myocardial tissue tagging with cardiovascular magnetic resonance.”
Author(s): Shehata, Monda L; Cheng, Susan; Osman, Nael F; Bluemke, David A; Lima, Joao A C
Source: J Cardiovasc Magn Reson Volume: 11 Pages: 55 Published: 2009

[10] Title: Characterization of three-dimensional myocardial deformation in the mouse heart: an MR tagging study.
Author(s): Zhong, Jia, Liu, Wei, Yu, Xin
Source: J Magn Reson Imaging Volume: 27 Issue: 6 Pages: 1263-70 Published: 2008

[11] Title: “Early manifestation of alteration in cardiac function in dystrophin deficient mdx mouse using 3D CMR tagging.”
Author(s): Li, Wei, Liu, Wei, Zhong, Jia, et al.
Source: J Cardiovasc Magn Reson Volume: 11 Pages: 40 Published: 2009 22

[12] “Regional assessment of left ventricular torsion by CMR tagging.”
Author(s): Russel, Iris K; Gotte, Marco J; Kuijer, Joost P; Marcus, J Tim
Source: J Cardiovasc Magn Reson Volume: 10 Pages: 26 Published: 2008

[13] “Title: CMR Predictors of Mitral Regurgitation in Mitral Valve Prolapse.”
Author(s): Delling, Francesca N, Kang, Lih Lisa, Yeon, Susan B, et al.
Source: JACC Cardiovasc Imaging Volume: 3 Issue: 10 Pages: 1037-45 Published: 2010

[14] “Altered myocardial motion pattern in Fabry patients assessed with CMR-tagging.”
Author(s): Rutz, Andrea K, Juli, Christoph F, Ryf, Salome, et al.
Source: J Cardiovasc Magn Reson Volume: 9 Issue: 6 Pages: 891-8 Published: 2007

[15] Title: “Septal ablation in hypertrophic obstructive cardiomyopathy improves systolic myocardial function in the lateral (free) wall: a follow-up study using CMR tissue tagging and 3D strain analysis.”
Author(s): van Dockum, Willem G, Kuijer, Joost P A, Gotte, Marco J W, et al.
Source: Eur Heart J Volume: 27 Issue: 23 Pages: 2833-9 Published: 2006 (EPubDate 2006 10)

[16] “A dynamic elastic model for segmentation and tracking of the heart in MR image sequences.”
Author(s): Schaerer, Joel; Casta, Christopher; Pousin, Jerome; Clarysse, Patrick
Source: Med Image Anal Volume: 14 Issue: 6 Pages: 738-49 Published: 2010 Dec

[17] “Collaborative tracking for MRI-guided robotic intervention on the beating heart.”
Author(s): Zhou, Y; Yeniaras, E; Tsiamyrtzis, P; Tsekos, N; Pavlidis, I
Source: Med Image Comput Comput Assist Interv Volume: 13 Issue: Pt 3 Pages: 351-8 Published: 2010

[18] “Three-dimensional speckle-tracking imaging for left ventricular rotation measurement: an in vitro validation study.”
Author(s): Zhou, Zhiwen; Ashraf, Muhammad; Hu, Dayi; Dai, Xiaonan; Xu, Yawei; Kenny, Bill; Cameron, Berkley; Nguyen, Thuan; Xiong, Li; Sahn, David J
Source: J Ultrasound Med Volume: 29 Issue: 6 Pages: 903-9 Published: 2010 Jun

[19] “Transmural myocardial strain in mouse: quantification of high-resolution MR tagging using harmonic phase (HARP) analysis.”
Author(s): Zhong, Jia, Liu, Wei, Yu, Xin
Source: Magn Reson Med Volume: 61 Issue: 6 Pages: 1368-73 Published: 2009

[20] “Quantification in cardiac MRI: advances in image acquisition and processing”
Anil K. Attili, Andreas Schuster, Eike Nagel, Johan H. C. Reiber and Rob J. van der Geest
The International Journal of Cardiovascular Imaging (formerly Cardiac Imaging)
Volume 26, Supplement 1, 27-40

Back to nature… sort of…

London (2010)

arlier today I watched with great patience this wonderful new interview with PZ Myers (thanks, Thunderf00t!), who spoke about his hugely popular science blog. I very much enjoy his site in which he started writing only 7 years ago. It was about 6 years ago that I started my own science blog (on computer vision) and later started another one about my particular area of focus (that was in 2005). They grew nicely and reached the niche whose narrow topic of interest they covered.

I have been thinking recently of the potential to inform people who are my peers through scientific blogs and decided that I will probably restore activity in those older two, as well as this one neglected personal blog where I hardly wrote anything for the past 3 years (it totals 1416 posts though, mostly from the olden days).

I found it gratifying back in the days around 2006 when people in my scientific field knew me in conferences because of my blogs and wanted to hang out with me because of these. The readership grew steadily as long as I kept writing. PZ Myers sees the same type of trend and Techrights, where I wrote over 11,000 posts, is the same. Perhaps I will resume posting in blog form about science later this month or next month. As always, I will separate my professional life, my personal life, and my hobbies (the 4 blogs I run will provide this separation).

On several occasions I was offered an opportunity to write a book, but frankly, I believe that books are seeing their end of days (when older generations are no longer with us, then pen and paper too may vanish). I was fortunate to get into blogging early on, thanks to Free software. It’s a rewarding experience even through there is no pay.

Several days ago I found this excellent YouTube channel of an anonymous British scientist. I strongly recommend it to anyone. Here is one of the 37 videos in this channel.