Real-time standard scan plane detection and localisation in fetal ultrasound using fully convolutional neural networks

Fetal mid-pregnancy scans are typically carried out according to fixed protocols. Accurate detection of abnormalities and correct biometric measurements hinge on the correct acquisition of clearly defined standard scan planes. Locating these standard planes requires a high level of expertise. However, there is a worldwide shortage of expert sonographers. In this paper, we consider a fully automated system based on convolutional neural networks which can detect twelve standard scan planes as defined by the UK fetal abnormality screening programme. The network design allows real-time inference and can be naturally extended to provide an approximate localisation of the fetal anatomy in the image. Such a framework can be used to automate or assist with scan plane selection, or for the retrospective retrieval of scan planes from recorded videos. The method is evaluated on a large database of 1003 volunteer mid-pregnancy scans. We show that standard planes acquired in a clinical scenario are robustly detected with a precision and recall of 69 % and 80 %, which is superior to the current state-of-the-art. Furthermore, we show that it can retrospectively retrieve correct scan planes with an accuracy of 71 % for cardiac views and 81 % for non-cardiac views

COCO_TS Dataset: Pixel-level Annotations Based on Weak Supervision for Scene Text Segmentation

The absence of large scale datasets with pixel-level supervisions is a significant obstacle for the training of deep convolutional networks for scene text segmentation. For this reason, synthetic data generation is normally employed to enlarge the training dataset. Nonetheless, synthetic data cannot reproduce the complexity and variability of natural images. In this paper, a weakly supervised learning approach is used to reduce the shift between training on real and synthetic data. Pixel-level supervisions for a text detection dataset (i.e. where only bounding-box annotations are available) are generated. In particular, the COCO-Text-Segmentation (COCO_TS) dataset, which provides pixel-level supervisions for the COCO-Text dataset, is created and released. The generated annotations are used to train a deep convolutional neural network for semantic segmentation. Experiments show that the proposed dataset can be used instead of synthetic data, allowing us to use only a fraction of the training samples and significantly improving the performances

Anveshak - A Groundtruth Generation Tool for Foreground Regions of Document Images

We propose a graphical user interface based groundtruth generation tool in this paper. Here, annotation of an input document image is done based on the foreground pixels. Foreground pixels are grouped together with user interaction to form labeling units. These units are then labeled by the user with the user defined labels. The output produced by the tool is an image with an XML file containing its metadata information. This annotated data can be further used in different applications of document image analysis.Comment: Accepted in DAR 201

An Image-Based Measure for Evaluation of Mathematical Expression Recognition

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38628-2_81Mathematical expression recognition is an active research field that is related to document image analysis and typesetting. In this study, we present a novel global performance evaluation measure for mathematical expression recognition based on image matching. Using an image representation for evaluation tries to overcome the representation ambiguity as human beings do. The results of a recent competition were used to perform several experiments in order to analyze the benefits and drawbacks of this measure.This work was partially supported by the Spanish MEC under the STraDA research project (TIN2012-37475-C02-01), the MITTRAL (TIN2009-14633-C03-01) project, the FPU grant (AP2009-4363), by the Generalitat Valenciana under the grant Prometeo/2009/014, and through the EU 7th Framework Programme grant tranScriptorium (Ref: 600707)Álvaro Muñoz, F.; Sánchez Peiró, JA.; Benedí Ruiz, JM. (2013). An Image-Based Measure for Evaluation of Mathematical Expression Recognition. En Pattern Recognition and Image Analysis. Springer. 682-690. https://doi.org/10.1007/978-3-642-38628-2_81S682690Álvaro, F., Sánchez, J.A., Benedí, J.M.: Unbiased evaluation of handwritten mathematical expression recognition. In: Proceedings of ICFHR, Italy, pp. 181–186 (2012)Chan, K.F., Yeung, D.Y.: Error detection, error correction and performance evaluation in on-line mathematical expression recognition. Pattern Recognition 34(8), 1671–1684 (2001)Chou, P.A.: Recognition of equations using a two-dimensional stochastic context-free grammar. In: Pearlman, W.A. (ed.) Visual Communications and Image Processing IV. SPIE Proceedings Series, vol. 1199, pp. 852–863 (1989)Garain, U., Chaudhuri, B.B.: A corpus for OCR research on mathematical expressions. Int. Journal on Document Analysis and Recognition 7, 241–259 (2005)Keysers, D., Deselaers, T., Gollan, C., Ney, H.: Deformation models for image recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 29(8), 1422–1435 (2007)Mouchére, H., Viard-Gaudin, C., Garain, U., Kim, D.H., Kim, J.H.: ICFHR 2012 – Competition on Recognition of On-line Mathematical Expressions (CROHME 2012). In: Proceedings of ICFHR, Italy, pp. 807–812 (2012)Otsu, N.: A Threshold Selection Method from Gray-level Histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)Sain, K., Dasgupta, A., Garain, U.: EMERS: a tree matching-based performance evaluation of mathematical expression recognition system. International Journal of Document Analysis and Recognition (2010)Toselli, A.H., Juan, A., Vidal, E.: Spontaneous Handwriting Recognition and Classification. In: Proceedings of ICPR, England, UK, pp. 433–436 (2004)Zanibbi, R., Blostein, D., Cordy, J.R.: Recognizing mathematical expressions using tree transformation. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(11), 1–13 (2002)Zanibbi, R., Pillay, A., Mouchere, H., Viard-Gaudin, C., Blostein, D.: Stroke-based performance metrics for handwritten mathematical expressions. In: Proceedings of ICDAR, pp. 334–338 (2011

Coulomb and nuclear breakup of a halo nucleus 11Be

Breakup reactions of the one-neutron halo nucleus 11Be on Pb and C targets at about 70 MeV/u have been investigated by measuring the momentum vectors of the incident 11Be, outgoing 10Be, and neutron in coincidence. The relative energy spectra as well as the angular distributions of the 10Be+n center of mass have been extracted for both targets. For the breakup on Pb target, the selection of forward scattering angles is found to be effective to extract almost purely the first-order E1 Coulomb breakup component, and to exclude the nuclear contribution and higher-order Coulomb breakup components. This angle-selected energy spectrum is thus used to deduce the spectroscopic factor for the 10Be(0+) 2s_1/2 configuration in 11Be which is found to be 0.72+-0.04 with B(E1) up to Ex=4 MeV of 1.05+-0.06 e2fm2. The energy weighted E1 strength up to Ex=4 MeV explains 70+-10% of the cluster sum rule, consistent with the obtained spectroscopic factor. The non-energy weighted sum rule is used to extract the root mean square distance of the halo neutron to be 5.77(16) fm, consistent with previously known values. In the breakup with C target, we have observed the excitations to the known unbound states in 11Be at Ex=1.78 MeV and 3.41 MeV. Angular distributions for these states show the diffraction pattern characteristic of L=2 transitions, resulting in J^pi =(3/2,5/2)+ assignment for these states. We finally find that even for the C target the E1 Coulomb direct breakup mechanism becomes dominant at very forward angles.Comment: 14 pages, 7 figures, accepted for publication on Physical Review

Noncommutative Chern-Simons Soliton

We have studied the noncommutative extension of the relativistic Chern-Simons-Higgs model, in the first non-trivial order in $\theta$, with only spatial noncommutativity. Both Lagrangian and Hamiltonian formulations of the problem have been discussed, with the focus being on the canonical and symmetric forms of the energy-momentum tensor. In the Hamiltonian scheme, constraint analysis and the induced Dirac brackets have been provided. The spacetime translation generators and their actions on the fields are discussed in detail. The effects of noncommutativity on the soliton solutions have been analysed thoroughly and we have come up with some interesting observations. Considering the {\it{relative}} strength of the noncommutative effects, we have shown that there is a universal character in the noncommutative correction to the magnetic field - it depends {\it{only}} on $\theta$. On the other hand, in the cases of all other observables of physical interest, such as the potential profile, soliton mass or the electric field, $\theta$ as well as $\tau$, (comprising solely of commutative Chern-Simons-Higgs model parameters), appear on similar footings. This phenomenon is a new finding which has come up in the present analysis. Lastly, we have pointed out a generic problem in the NC extension of the models, in the form of a mismatch between the BPS dynamical equation and the full variational equations of motion, to $O(\theta)$. This mismatch indicates that the analysis is not complete as it brings in to fore the ambiguities in the definition of the energy-momentum tensor in a noncommutative theory.Comment: 21 page

Image processing of cylinder wake generation

In the present study, image processing techniques are applied to the chronophotographic visualizations of a cylinder wake generation. The flow patterns obtained by means of tracer particles are digitalized and processed in order to characterize the flow. This characterization is carried out by determining the evolution of the geometric parameters governing the wake, together with the streamfunction, vorticity, and pressure distributions. The present study reaches the moment of shedding of the first pair of vortices

Measurement of Single and Double Spin-Flip Probabilities in Inelastic Deuteron Scattering on 12C at 270 MeV

The deuteron single and double spin-flip probabilities, S1 and S2, have been measured for the 12C(pol{d},pol{d}') reaction at Ed = 270 MeV for an excitation energy range between 4 and 24 MeV and a scattering angular range between Theta_lab = 2.5 and 7.5 deg. The extracted S1 exhibits characteristic values depending on the structure of the excited state. The S2 is close to zero over the measured excitation energy range. The SFP angular distribution data for the 2+ (4.44 MeV) and 1+ (12.71 MeV) states are well described by the microscopic DWIA calculations

Comparison of Interactions Between Control and Mutant Macrophages

This paper presents a preliminary study on macrophages migration in Drosophila embryos, comparing two types of cells. The study is carried out by a framework called macrosight which analyses the movement and interaction of migrating macrophages. The framework incorporates a segmentation and tracking algorithm into analysing motion characteristics of cells after contact. In this particular study, the interactions between cells is characterised in the case of control embryos and Shot3 mutants, where the cells have been altered to suppress a specific protein, looking to understand what drives the movement. Statistical significance between control and mutant cells was found when comparing the direction of motion after contact in specific conditions. Such discoveries provide insights for future developments in combining biological experiments to computational analysis

Biografo: An integrated tool for forensic writer identification

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-20125-2_17The design and performance of a practical integrated tool for writer identification in forensic scenarios is presented. The tool has been designed to help forensic examiners along the complete identification process: from the data acquisition to the recognition itself, as well as with the management of large writer-related databases. The application has been implemented using JavaScript running over a relational database which provides the whole system with some very desirable and unique characteristics such as the possibility to perform all type of queries (e.g., find individuals with some very discriminative character, find a specific document, display all the samples corresponding to one writer, etc.), or a complete control over the set of parameters we want to use in a specific recognition task (e.g., users in the database to be used as control set, set of characters to be used in the identification, size of the ranked list we want as final result, etc.). The identification performance of the tool is evaluated on a real-case forensic database showing some very promising results.This work has been partially supported by the Spanish Dirección General de la Guardia Civil, and projects Contexts (S2009/TIC-1485) from CAM, Bio-Challenge (TEC2009-11186) from Spanish MICINN, BBfor2 (ITN-2008-238803) from the European Commision, and Cátedra UAM-Telefónica