Medical image processing @ Research Platforms

Post by: Jasamine Coles-Black

Hello everyone! I’m Jas, your new Research Community Coordinator for 3D Slicer at Research Platforms.

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I first came into contact with Research Platforms via 3D Med, a joint collaboration in medical 3D printing with Austin Health, founded by ResPlat legend Paul Mignone and vascular surgeon Jason Chuen. This initiative included the “3D Printing for Medical Applications Seminar”, and led me to enrol in Louise van der Werff’s 3D Slicer Alpha workshop last year. For those of you who don’t know, 3D Slicer is a software package for image analysis and scientific visualisation. The best part? It’s free!

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A kidney tumour model segmented from a patient’s CT scan at Austin Health using 3D Slicer, to aid presurgical planning. Watch this space for the 3D printed end result!

Just a little bit about my background. I’m an aspiring surgeon in my final year at Melbourne Medical School. It was this interest in surgery that led to me to discover the medical applications of 3D printing, which are varied and far ranging, and all equally amazing.

Some pretty inspiring examples in the literature would include bioengineering and tissue engineering, interventional planning, medical and surgical training, anatomy teaching, customised prostheses and implantable components, patient education, and forensic medicine.

As someone with who struggles with Microsoft Word, and had no previous medical image processing experience, this for me was truly diving off the deep end. For someone of my background, the promised land was truly far, far away. And like many clinicians, I was initially unsure about how much benefit medical image processing could truly bring to my research.

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This leads me to my point - while there seems to be a huge amount of enthusiasm for the applications of 3D printing in the wider medical community, a significant barrier remains. Despite their enthusiasm, clinicians often lack the technical skills required to segment medical images and 3D print models of their patient’s anatomy.

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A generalised 3D printing workflow for medical models.image

The generalised 3D printing workflow conundrum facing clinicians.

Following this initial experience, I continued to collaborate with Research Platforms as a Helper for 3D Slicer. It was during this time that I truly began to appreciate what Research Platforms was all about – namely, free training to help you do your research better, with as few barriers as possible.

This too, has been my goal with the 3D Med initiative based at Austin Health – information and technical know-how about medical image processing and 3D printing should be made available to as many clinicians as possible who are interested in applying this technology to their research.

Surgeons as a whole have a pervasive reputation for being luddites. While this can sometimes be true, the 2016 Royal Australasian College of Surgeons Annual Scientific Congress in Brisbane set out to change this perception, with the theme “Surgery, Technology and Communication”.

I’ve just returned to Melbourne, fresh faced and inspired by the work of the myriad of amazing local and international speakers invited to present at the congress. Themes that were raised during this conference included big data and data management, novel methods of teaching trainee surgeons, virtual and augmented reality, and 3D printing (if you haven’t figured it out by now, it’s kind of my personal interest).

Other fascinating topics that were raised included the use of robotics and simulation in surgery, with processed medical images being used as the inputs for the surgical robots to do their thing.

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Is it just me, or does it seem as though more surgeons ought to be visiting us here at Research Platforms? :D

Soooooooooooooooooooo… What can you do for me, Jas?

Well, I’m glad you asked! As one of the Research Community Coordinators for 3D Slicer, I’ve been tasked with upskilling the medical research community in medical image processing, 3D modelling, and 3D printing. At Research Platforms we’re also all about collaboration and network building. In essence, I’d also like to put you in touch with other individuals with similar interests, but complementary skill sets, so you can scratch each other’s backs like happy lab monkeys.

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Scratch that collaborative research itch!

And to all 3D Slicer course alumni: how have you been using 3D Slicer in your research? Having attended the introductory 3D Slicer for Beginners course, have you got any suggestions for intermediate/advanced extension courses that’ll help you do your research better? We’d love to hear from you!

I can be reached at: jasaminecb@gmail.com or send a tweet my way @jasaminecb - I look forward to hearing from you!

3D Slicer Alpha Training Summary

By Louise van der Werff

Last week I ran my newly developed 3D Slicer training workshop over three content-packed afternoons. Five willing participants were able to come along and get their first peek at the training material, provide very helpful feedback related to the structure of the workshop, and brainstorm ways in which this software may be harnessed in their own work.

For those who may not be familiar with 3D Slicer, it is an open source software package for image visualisation and analysis. More specifically, 3D Slicer is tailored towards the analysis of medical scan data such as that generated via MRI and CT scans. Although 3D Slicer has a wide range of functionalities, this workshop was primarily focussed on generating 3 dimensional volume renderings and surface models of anatomical features from medical scan data.

After giving an introduction on the principles of image processing, I conducted a tour of the 3D Slicer graphical interface, then gave the participants a series of challenges to generate 3D surface models of different anatomical features.

The first step towards generating a 3D model involves image segmentation, which is the process of separating an image into distinct components to make it more meaningful for software to analyse. This is done by assigning each pixel belonging to a particular object a label.

Segmentation of a photo into three distinct components. 

Anatomical structures are segmented from medical scan datasets in 3D Slicer by generating a labelmap over the feature of interest. Anatomical structures we segmented during the workshop included bone, lungs, airways, lateral ventricles, and a trachea and larynx. We explored both manual and automated segmentation methods, their appropriateness being predominantly dependent on the level of contrast between the feature of interest and the surrounding volume.

A particularly challenging case was manually segmenting the trachea and larynx from an MRI scan. Below is a picture of the original scan data, the segmented labelmap, the generated 3D model, and a 3D print of the model to-scale.

An MRI scan of a child’s trachea and larynx. These were manually segmented before a 3D surface model was generated and then 3D printed to scale. 

In addition to segmentation, we also touched upon basic image registration, adding annotations such as fiducials and rulers to a dataset, using statistical tools to calculate volumes of segmented regions, and creating scene views.

The generation of 3D models of anatomical features may be beneficial to many researchers and clinicians, for teaching and training purposes, surgical planning, the creation of custom fit implants and prosthetics, and simple visualisation.

As well as using local installs of 3D Slicer on laptops, we are also currently exploring the effectiveness of running 3D Slicer from the NeCTAR Research Cloud via resbaz.cloud.edu.au (which is powered by the DIT4C engine). A couple of participants tried this approach out with promising results. One major benefit of running graphically intensive software from the cloud is that performance is not limited to the specifications of  local devices, and resources can be scaled as required.

Major points of feedback from this alpha 3D Slicer workshop was that participants preferred more practical content to theory, and wanted to get hands-on with the software as quickly as possible. It was great to see ideas flowing near the end of the workshop from participants about how they might apply 3D Slicers functionalities to their own research projects. Some participants were also interested in exploring whether 3D Slicer could be applied to non-medical applications, such as in the Materials Engineering field.

The alpha training material can be viewed and commented on here.

Please keep an eye out for more training sessions, soon to be announced! If you have any questions, please don’t helistate to contact me at louisevanderwerff@gmail.com or tweet me @LouWerff.

3D Slicer Alpha Training Workshop

by Louise van der Werff

Following my last blog post, I have been busy meeting members of the community and developing training material for the new 3D Slicer workshops soon to be on offer via the Research Bazaar. It’s getting to the point where I would love to share some of this material with the community, but the content and pace of the course is far from polished.

Thus I am on the search for a few willing participants (aka. guinea pigs) to come along and be a part of my alpha training workshop. This workshop will not run smoothly, there will be ‘bugs’, and it will be incomplete. This is an opportunity to gain constructive feedback and guidance from others regarding the content, pace, and length of the workshop.

Image: Volume rendering of a DICOM dataset using 3D Slicer

Below is an 'expression of interest’ form, which you can fill out if you are interested in being part of the alpha training.

Th workshop will be run across three consecutive afternoons (Tuesday the 21st, Wednesday the 22nd and Thursday the 23rd of July) from 3pm - 5pm in the Doug McDonnell building (Level 3) at Melbourne University. All participants are invited to hang around for a drink (coffee/tea/beer/wine) after each session to provide feedback.

There are only a limited number of spots available, and we will try to pick a complimentary team from those who have expressed their interest. I will contact interested parties by Tuesday the 14th of July to let them know if they can attend. If you don’t get picked, don’t worry, a larger, beta training session will be organised soon after.

If you have any questions, please don’t hesitate to contact myself, at louisevanderwerff@gmail.com, David F Flanders at dff.melb@gmail.com

Meet Louise - 3D Modelling Medical Scans!

Hello all,

My name is Louise and I am the newest member of the Research Bazaar team, having just started as a Research Community Coordinator with the team at Research Platform.

After completing a Bachelor of Science and a Bachelor of Engineering (Materials) at Monash University in 2008, I went on to do a PhD in collaboration with Monash University, CSIRO, and Smith & Nephew. During my PhD I developed novel multi-component composite fibres with thermochromic behaviour. In other words, they changed colour with temperature changes (think mood rings in fibre form). Tuned to work in the physiological temperature range, these fibres were created as a potential method for thermal mapping of wounds beds, via their incorporation into bandages.

Later down the track, I was involved in a Researcher in Business program within CSIRO, helping Australian medical devices company Anatomics develop their porous polyethylene surgical implant material PoreStar. Outside of academia I have pursued my own developing interest in 3D printing by purchasing a Makerbot Replicator 2X, combining my knowledge and interest in polymer processing with my passion for DIYing and craft. With this new and exciting piece of hardware I taught myself some rudimentary 3D modelling skills and combined 3D printing with silicone moulding, epoxy resin casting, and general crafty inspiration to come up with some cool new products I now sell online and at markets under the brand name Wordosaurus Text.

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a. my Makerbot replicator 2X, b. a treble clef 3D model in MakerWare c. a silicone mould of the 3D printed master shapes d. A final epoxy resin cast.

I have joined the ResBaz team at Research Platforms to develop awareness and run training sessions relating to medical image processing, in particular the generation of 3D models from medical scan data in the DICOM file format. DICOM image files are produced by a range of medical imaging equipment, (MRI, CT, PET, XRay etc), and consist of a series or stack of cross-sectional image slices across a region of interest in the body. By combining these slices a 3 dimensional representation of the body can be generated.

Generating 3D models of anatomical features from DICOM image files can be beneficial in multiple scenarios. Physical 3D prints of anatomical features such as bones may be used for teaching or training purposes, for the planning of a complex surgery to reduce overall theatre time and risk, and for the creation of implants custom designed and fit to a particular patient. The “3D Printing for Medical Applications” seminar (#3DMed), held on the 14th of April this year, highlighted many applications in which this functionality has been harnessed, and how it could be harnessed in the future.

The software around which the training will be designed is 3D Slicer, an open source community platform with a wide range of capabilities. It’s modular nature provides flexibility and the ability to add on new functionalities as required.  It’s interactive visualisation capabilities includes the ability to display arbitrarily oriented image slices; segment, label features and generate colourmaps, and render 3D models of desired anatomical structures.

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Screenshot taken within 3D Slicer from inbuilt example dataset ‘CTChest’

As this training course is in the very early stages of development, there is ample opportunity for community input and feedback in regards to the content of the material covered. This course is intended to provide researchers and medical staff with valuable and relevant image processing and 3D modelling skills. If you feel you would benefit from this course, or if you know somebody who might, please feel free to contact me to discuss your requirements, at louisevanderwerff@gmail.com, or tweet me at @LouWerff.

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