Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?; and, 2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset.The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch.Comment: 8 pages, 3 figure

Validation of Tissue Modelization and Classification Techniques in T1-Weighted MR Brain Images

We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this validation study. Two of them are based on Finite Gaussian Mixture (FGM) model. The first one consists only in pure gaussian distributions (FGM-EM). The second one uses a different model for partial volume (PV) (FGM-GA). The third one is based on a Hidden Markov Random Field (HMRF) model. All methods have been tested on a Digital Brain Phantom image considered as the ground truth. Noise and intensity non-uniformities have been added to simulate real image conditions. Also the effect of an anisotropic filter is considered. Results demonstrate that methods relying in both intensity and spatial information are in general more robust to noise and inhomogeneities. However, in some cases there is no significant differences between all presented methods

Stability of Top-Points in Scale Space

Abstract. This paper presents an algorithm for computing stability of top-points in scale-space. The potential usefulness of top-points in scalespace has already been shown for a number of applications, such as image reconstruction and image retrieval. In order to improve results only reliable top-points should be used. The algorithm is based on perturbation theory and noise propagation

The human eye-movement response to maintained surface galvanic vestibular stimulation

Contains fulltext : 141356.pdf (publisher's version ) (Closed access

Omineca Herald, October, 04, 1979

The relation between progression of cerebral small vessel disease (SVD) and gait decline is uncertain, and diffusion tensor imaging (DTI) studies on gait decline are lacking. We therefore investigated the longitudinal associations between (micro) structural brain changes and gait decline in SVD using DTI. 275 participants were included from the Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort (RUN DMC), a prospective cohort of participants with cerebral small vessel disease aged 50–85years. Gait (using GAITRite) and magnetic resonance imaging measures were assessed during baseline (2006–2007) and follow-up (2011−2012). Linear regression analysis was used to investigate the association between changes in conventional magnetic resonance and diffusion tensor imaging measures and gait decline. Tract-based spatial statistics analysis was used to investigate region-specific associations between changes in white matter integrity and gait decline. 56.2% were male, mean age was 62.9years (SD8.2), mean follow-up duration was 5.4years (SD0.2) and mean gait speed decline was 0.2m/s (SD0.2). Stride length decline was associated with white matter atrophy (β=0.16, p=0.007), and increase in mean white matter radial diffusivity and mean diffusivity, and decrease in mean fractional anisotropy (respectively, β=−0.14, p=0.009; β=−0.12, p=0.018; β=0.10, p=0.049), independent of age, sex, height, follow-up duration and baseline stride length. Tract-based spatial statistics analysis showed significant associations between stride length decline and fractional anisotropy decrease and mean diffusivity increase (primarily explained by radial diffusivity increase) in multiple white matter tracts, with the strongest associations found in the corpus callosum and corona radiata, independent of traditional small vessel disease markers. White matter atrophy and loss of white matter integrity are associated with gait decline in older adults with small vessel disease after 5years of follow-up. These findings suggest that progression of SVD might play an important role in gait decline. Keywords: Cerebral small vessel disease (SVD), MRI, Diffusion tensor imaging (DTI), Tract-based spatial statistics (TBSS), Gai

The glutathione biosynthetic pathway of Plasmodium is essential for mosquito transmission

1Infection of red blood cells (RBC) subjects the malaria parasite to oxidative stress. Therefore, efficient antioxidant and redox systems are required to prevent damage by reactive oxygen species. Plasmodium spp. have thioredoxin and glutathione (GSH) systems that are thought to play a major role as antioxidants during blood stage infection. In this report, we analyzed a critical component of the GSH biosynthesis pathway using reverse genetics. Plasmodium berghei parasites lacking expression of gamma-glutamylcysteine synthetase (γ-GCS), the rate limiting enzyme in de novo synthesis of GSH, were generated through targeted gene disruption thus demonstrating, quite unexpectedly, that γ-GCS is not essential for blood stage development. Despite a significant reduction in GSH levels, blood stage forms of pbggcs− parasites showed only a defect in growth as compared to wild type. In contrast, a dramatic effect on development of the parasites in the mosquito was observed. Infection of mosquitoes with pbggcs− parasites resulted in reduced numbers of stunted oocysts that did not produce sporozoites. These results have important implications for the design of drugs aiming at interfering with the GSH redox-system in blood stages and demonstrate that de novo synthesis of GSH is pivotal for development of Plasmodium in the mosquito

When Music and Long-Term Memory Interact: Effects of Musical Expertise on Functional and Structural Plasticity in the Hippocampus

The development of musical skills by musicians results in specific structural and functional modifications in the brain. Surprisingly, no functional magnetic resonance imaging (fMRI) study has investigated the impact of musical training on brain function during long-term memory retrieval, a faculty particularly important in music. Thus, using fMRI, we examined for the first time this process during a musical familiarity task (i.e., semantic memory for music). Musical expertise induced supplementary activations in the hippocampus, medial frontal gyrus, and superior temporal areas on both sides, suggesting a constant interaction between episodic and semantic memory during this task in musicians. In addition, a voxel-based morphometry (VBM) investigation was performed within these areas and revealed that gray matter density of the hippocampus was higher in musicians than in nonmusicians. Our data indicate that musical expertise critically modifies long-term memory processes and induces structural and functional plasticity in the hippocampus

Nonlinear temporal dynamics of cerebral small vessel disease: The RUN DMC study

Objective: To investigate the temporal dynamics of cerebral small vessel disease (SVD) by 3 consecutive assessments over a period of 9 years, distinguishing progression from regression. Methods: Changes in SVD markers of 276 participants of the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC) cohort were assessed at 3 time points over 9 years. We assessed white matter hyperintensities (WMH) volume by semiautomatic segmentation and rated lacunes and microbleeds manually. We categorized baseline WMH severity as mild, moderate, or severe according to the modified Fazekas scale. We performed mixed-effects regression analysis including a quadratic term for increasing age. Results: Mean WMH progression over 9 years was 4.7 mL (0.54 mL/y; interquartile range 0.95–5.5 mL), 20.3% of patients had incident lacunes (2.3%/y), and 18.9% had incident microbleeds (2.2%/y). WMH volume declined in 9.4% of the participants during the first follow-up interval, but only for 1 participant (0.4%) throughout the whole follow-up. Lacunes disappeared in 3.6% and microbleeds in 5.7% of the participants. WMH progression accelerated over time: including a quadratic term for increasing age during follow-up significantly improved the model (p < 0.001). SVD progression was predominantly seen in participants with moderate to severe WMH at baseline compared to those with mild WMH (odds ratio [OR] 35.5, 95% confidence interval [CI] 15.8–80.0, p < 0.001 for WMH progression; OR 5.7, 95% CI 2.8–11.2, p < 0.001 for incident lacunes; and OR 2.9, 95% CI 1.4–5.9, p = 0.003 for incident microbleeds). Conclusions: SVD progression is nonlinear, accelerating over time, and a highly dynamic process, with progression interrupted by reduction in some, in a population that on average shows progression.A. Tuladhar is a junior staff member of the Dutch Heart Foundation (grant 2016T044). E. van Dijk received a personal fellowship from the Dutch Brain Foundation (H04-12; F2009[1]-16). L. Rutten-Jacobs is supported by a British Heart Foundation Immediate Research Fellowship (FS/15/61/31626). C. Klijn is supported by a clinical established investigator grant of the Dutch Heart Foundation (grant 2012 T077) and an Aspasia grant from The Netherlands Organisation for Health Research and Development (ZonMw grant 015.008.048). F. de Leeuw is supported by a clinical established investigator grant of the Dutch Heart Foundation (grant 2014 T060), by a VIDI innovational grant from The Netherlands Organisation for Health Research and Development (ZonMw grant 016.126.351), and the MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente

miR-132 Enhances Dendritic Morphogenesis, Spine Density, Synaptic Integration, and Survival of Newborn Olfactory Bulb Neurons

An array of signals regulating the early stages of postnatal subventricular zone (SVZ) neurogenesis has been identified, but much less is known regarding the molecules controlling late stages. Here, we investigated the function of the activity-dependent and morphogenic microRNA miR-132 on the synaptic integration and survival of olfactory bulb (OB) neurons born in the neonatal SVZ. In situ hybridization revealed that miR-132 expression occurs at the onset of synaptic integration in the OB. Using in vivo electroporation we found that sequestration of miR-132 using a sponge-based strategy led to a reduced dendritic complexity and spine density while overexpression had the opposite effects. These effects were mirrored with respective changes in the frequency of GABAergic and glutamatergic synaptic inputs reflecting altered synaptic integration. In addition, timely directed overexpression of miR-132 at the onset of synaptic integration using an inducible approach led to a significant increase in the survival of newborn neurons. These data suggest that miR-132 forms the basis of a structural plasticity program seen in SVZ-OB postnatal neurogenesis. miR-132 overexpression in transplanted neurons may thus hold promise for enhancing neuronal survival and improving the outcome of transplant therapies