Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks

There is a common belief that the successful training of deep neural networks requires many annotated training samples, which are often expensive and difficult to obtain especially in the biomedical imaging field. While it is often easy for researchers to use data augmentation to expand the size of training sets, constructing and generating generic augmented data that is able to teach the network the desired invariance and robustness properties using traditional data augmentation techniques is challenging in practice. In this paper, we propose a novel automatic data augmentation method that uses generative adversarial networks to learn augmentations that enable machine learning based method to learn the available annotated samples more efficiently. The architecture consists of a coarse-to-fine generator to capture the manifold of the training sets and generate generic augmented data. In our experiments, we show the efficacy of our approach on a Magnetic Resonance Imaging (MRI) image, achieving improvements of 3.5% Dice coefficient on the BRATS15 Challenge dataset as compared to traditional augmentation approaches. Also, our proposed method successfully boosts a common segmentation network to reach the state-of-the-art performance on the BRATS15 Challenge

Physiology-based simulation of the retinal vasculature enables annotation-free segmentation of OCT angiographs

Optical coherence tomography angiography (OCTA) can non-invasively image the eye's circulatory system. In order to reliably characterize the retinal vasculature, there is a need to automatically extract quantitative metrics from these images. The calculation of such biomarkers requires a precise semantic segmentation of the blood vessels. However, deep-learning-based methods for segmentation mostly rely on supervised training with voxel-level annotations, which are costly to obtain. In this work, we present a pipeline to synthesize large amounts of realistic OCTA images with intrinsically matching ground truth labels; thereby obviating the need for manual annotation of training data. Our proposed method is based on two novel components: 1) a physiology-based simulation that models the various retinal vascular plexuses and 2) a suite of physics-based image augmentations that emulate the OCTA image acquisition process including typical artifacts. In extensive benchmarking experiments, we demonstrate the utility of our synthetic data by successfully training retinal vessel segmentation algorithms. Encouraged by our method's competitive quantitative and superior qualitative performance, we believe that it constitutes a versatile tool to advance the quantitative analysis of OCTA images

Automated claustrum segmentation in human brain MRI using deep learning

In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function. However, relatively few in vivo studies of the claustrum exist in humans. A reason for this may be the delicate and sheet-like structure of the claustrum lying between the insular cortex and the putamen, which makes it not amenable to conventional segmentation methods. Recently, Deep Learning (DL) based approaches have been successfully introduced for automated segmentation of complex, subcortical brain structures. In the following, we present a multi-view DL-based approach to segment the claustrum in T1-weighted MRI scans. We trained and evaluated the proposed method in 181 individuals, using bilateral manual claustrum annotations by an expert neuroradiologist as reference standard. Cross-validation experiments yielded median volumetric similarity, robust Hausdorff distance, and Dice score of 93.3%, 1.41 mm, and 71.8%, respectively, representing equal or superior segmentation performance compared to human intra-rater reliability. The leave-one-scanner-out evaluation showed good transferability of the algorithm to images from unseen scanners at slightly inferior performance. Furthermore, we found that DL-based claustrum segmentation benefits from multi-view information and requires a sample size of around 75 MRI scans in the training set. We conclude that the developed algorithm allows for robust automated claustrum segmentation and thus yields considerable potential for facilitating MRI-based research of the human claustrum. The software and models of our method are made publicly available

Image-based modeling of tumor growth in patients with glioma.

International audienceno abstrac

On astrophysical solution to ultra high energy cosmic rays

We argue that an astrophysical solution to UHECR problem is viable. The pectral features of extragalactic protons interacting with CMB are calculated in model-independent way. Using the power-law generation spectrum $\propto E^{-\gamma_g}$ as the only assumption, we analyze four features of the proton spectrum: the GZK cutoff, dip, bump and the second dip. We found the dip, induced by electron-positron production on CMB, as the most robust feature, existing in energy range $1\times 10^{18} - 4\times 10^{19}$ eV. Its shape is stable relative to various phenomena included in calculations. The dip is well confirmed by observations of AGASA, HiRes, Fly's Eye and Yakutsk detectors. The best fit is reached at $\gamma_g =2.7$, with the allowed range 2.55 - 2.75. The dip is used for energy calibration of the detectors. After the energy calibration the fluxes and spectra of all three detectors agree perfectly, with discrepancy between AGASA and HiRes at $E> 1\times 10^{20}$ eV being not statistically significant. The agreement of the dip with observations should be considered as confirmation of UHE proton interaction with CMB. The dip has two flattenings. The high energy flattening at $E \approx 1\times 10^{19}$ eV automatically explains ankle. The low-energy flattening at $E \approx 1\times 10^{18}$ eV provides the transition to galactic cosmic rays. This transition is studied quantitatively. The UHECR sources, AGN and GRBs, are studied in a model-dependent way, and acceleration is discussed. Based on the agreement of the dip with existing data, we make the robust prediction for the spectrum at $1\times 10^{18} - 1\times 10^{20}$ eV to be measured in the nearest future by Auger detector.Comment: Revised version as published in Phys.Rev. D47 (2006) 043005 with a small additio

Evidence for the positive-strangeness pentaquark Θ+\Theta^+ in photoproduction with the SAPHIR detector at ELSA

The positive--strangeness baryon resonance $\Theta^+$ is observed in photoproduction of the $\rm nK^+K^0_s$ final state with the SAPHIR detector at the Bonn ELectron Stretcher Accelerator ELSA. It is seen as a peak in the $\rm nK^+$ invariant mass distribution with a $4.8\sigma$ confidence level. We find a mass $\rm M_{\Theta^+} = 1540\pm 4\pm 2$ MeV and an upper limit of the width $\rm \Gamma_{\Theta^+} < 25$ MeV at 90% c.l. From the absence of a signal in the $\rm pK^+$ invariant mass distribution in $\rm\gamma p\to pK^+K^-$ at the expected strength we conclude that the $\Theta^+$ must be isoscalar.Comment: 9 pages, 4 figure

Measurement of polarisation observables in Ks0Σ+K^0_s\Sigma^+ photoproduction off the proton

The reaction $\gamma \, p \rightarrow K^0_S\,\Sigma^+$ is studied in the photon energy range from threshold. Linearly polarised photon beams from coherent bremsstrahlung enabled the first measurement of photon beam asymmetries in this reaction up to $E_\gamma = 2250$ MeV. In addition, the recoil hyperon polarisation was determined through the asymmetry in the weak decay $\Sigma^+ \rightarrow p \pi^0$ up to $E_\gamma = 1650$ MeV. The data are compared to partial wave analyses, and the possible impact on the interpretation of a recently observed cusp-like structure near the $K^*$ thresholds is discussed.Comment: 6 pages, 5 figures. References [8,9,10,11] which were not on the original submission are now include

K0-Sigma+ Photoproduction with SAPHIR

Preliminary results of the analysis of the reaction p(gamma,K0)Sigma+ are presented. We show the first measurement of the differential cross section and much improved data for the total cross section than previous data. The data are compared with model predictions from different isobar and quark models that give a good description of p(gamma,K+)Lambda and p(gamma,K+)Sigma0 data in the same energy range. Results of ChPT describe the data adequately at threshold while isobar models that include hadronic form factors reproduce the data at intermediate energies.Comment: 4 pages, Latex2e, 4 postscript figures. Talk given at the International Conference on Hypernuclear and Strange Particle Physics (HYP97), Brookhaven National Laboratory, USA, October 13-18, 1997. To be published in Nucl. Phys. A. Revised version due to changes in experimental dat

Photoproduction of pi0 omega off protons for E(gamma) < 3 GeV

Differential and total cross-sections for photoproduction of gamma proton to proton pi0 omega and gamma proton to Delta+ omega were determined from measurements of the CB-ELSA experiment, performed at the electron accelerator ELSA in Bonn. The measurements covered the photon energy range from the production threshold up to 3GeV.Comment: 8 pages, 13 figure

In-medium ω\omega mass from the γ+Nb→π0γ+X\gamma + Nb \to \pi^{0}\gamma + X reaction

Data on the photoproduction of $\omega$ mesons on nuclei have been re-analyzed in a search for in-medium modifications. The data were taken with the Crystal Barrel(CB)/TAPS detector system at the ELSA accelerator facility in Bonn. First results from the analysis of the data set were published by D. Trnka et al. in Phys. Rev. Lett 94 (2005) 192303 \cite{david}, claiming a lowering of the $\omega$ mass in the nuclear medium by 14$$ at normal nuclear matter density. The extracted $\omega$ line shape was found to be sensitive to the background subtraction. For this reason a re-analysis of the same data set has been initiated and a new method has been developed to reduce the background and to determine the shape and absolute magnitude of the background directly from the data. Details of the re-analysis and of the background determination are described. The $\omega$ signal on the $Nb$ target, extracted in the re-analysis, does not show a deviation from the corresponding line shape on a $LH_2$ target, measured as reference. The earlier claim of an in-medium mass shift is thus not confirmed. The sensitivity of the $\omega$ line shape to different in-medium modification scenarios is discussed.Comment: 13 pages and 11 figures, submitted for publicatio