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An Update on Publications
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S of last night, a revised submission was sent to be considered for a special TMI issue on validation. This time, for a change, we included time estimates for ground-truth-free assessement on non-rigid registration in 3-D.
Concurrently, a related paper was accepted as an oral presentation in Medical Image Understanding and Analysis (MIUA) 2006. I will post a link to that paper as soon as I put it online.
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Conference Paper on Non-Rigid Registration (NRR) Validation
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Our paper to ISBI 2006 has just been accepted and it is available on-line as well:
Abstract:
E compare two methods for assessing the performance of groupwise non-rigid registration algorithms. One approach, which has been described previously, utilizes a measure of overlap between data labels. Our new approach exploits the fact that, given a set of non-rigidly registered images, a generative statistical appearance model can be constructed. We observe that the quality of the model depends on the quality of the registration, and can be evaluated by comparing synthetic images sampled from the model with the original image set. We derive indices of model specificity and generalisation that can be used to assess model/registration quality. We show that both approaches detect the loss of registration as a set of correctly registered MR images of the brain is progressively perturbed. We compare the sensitivities of the different methods and show that, as well as requiring no ground truth, our new specificity measure provides the most sensitive approach to detecting misregistration.
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Registration Assessment Abstract
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We shall be presenting our registration assessment work this Tuesday. A camera-ready version of the accompanying 2-page abstract is available on-line:
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Model Construction and Registration in Medical Imaging
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IPMI 2005 ended last week. Therein, many relevant concepts were explained with emphasis on automatic construction of appearance models and evaluation of registration. The power of the method was demonstrated by applying it to medical data, namely brain images.
See more details in the relevant papers
or follow the many links in the corresponding Web log item.
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It has come to my attention that Lewis Griffin and Tony
Chen of UCL will deliver a talk titled "Models, Registration & Segmentation United" 2 weeks from now in an Oxford Plenary Meeting. This is definitely something to look forward to as there are opportunities for discussions and exchange of ideas.
This strand of work also aims directly at the goals of the Grand Challenge.
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Simultaneous Segmentation, Registration and Models
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One paper of interest involves the employment of segmentation to improve non-rigid registration (NRR) and vice versa:
Chen Xiaohua, Michael Brady, Daniel Rueckert. "Simultaneous Segmentation and Registration for Medical Image". MICCAI 2004, pp. 663-670.
A later paper involves the unification of registration and model-building:
Carole J. Twining, Tim Cootes, Stephen Marsland, Vladimir Petrovic, Roy Schestowitz, and Chris J. Taylor. "A Unified Information-Theoretic Approach to Groupwise Non-Rigid Registration and Model Building". To appear in Information Processing in Medical Images (IPMI), 2005.
Much future work will rely on these developments.
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