Morphological and multi-level geometrical descriptor analysis in CT and MRI volumes for automatic pancreas segmentation

Automatic pancreas segmentation in 3D radiological scans is a critical, yet challenging task. As a prerequisite for computer-aided diagnosis (CADx) systems, accurate pancreas segmentation could generate both quantitative and qualitative information towards establishing the severity of a condition, and thus provide additional guidance for therapy planning. Since the pancreas is an organ of high inter-patient anatomical variability, previous segmentation approaches report lower quantitative accuracy scores in comparison to abdominal organs such as the liver or kidneys. This paper presents a novel approach for automatic pancreas segmentation in magnetic resonance imaging (MRI) and computer tomography (CT) scans. This method exploits 3D segmentation that, when coupled with geometrical and morphological characteristics of abdominal tissue, classifies distinct contours in tight pixel-range proximity as “pancreas” or “non-pancreas”. There are three main stages to this approach: (1) identify a major pancreas region and apply contrast enhancement to differentiate between pancreatic and surrounding tissue; (2) perform 3D segmentation via continuous max-flow and min-cuts approach, structured forest edge detection, and a training dataset of annotated pancreata; (3) eliminate non-pancreatic contours from resultant segmentation via morphological operations on area, structure and connectivity between distinct contours. The proposed method is evaluated on a dataset containing 82 CT image volumes, achieving mean Dice Similarity coefficient (DSC) of 79.3 ± 4.4%. Two MRI datasets containing 216 and 132 image volumes are evaluated, achieving mean DSC 79.6 ± 5.7% and 81.6 ± 5.1% respectively. This approach is statistically stable, reflected by lower metrics in standard deviation in comparison to state-of-the-art approaches

Advancing Pancreas Segmentation in Multi-protocol MRI Volumes using Hausdorff-Sine Loss Function

Computing pancreatic morphology in 3D radiological scans could provide significant insight about a medical condition. However, segmenting the pancreas in magnetic resonance imaging (MRI) remains challenging due to high inter-patient variability. Also, the resolution and speed of MRI scanning present artefacts that blur the pancreas bound- aries between overlapping anatomical structures. This paper proposes a dual-stage automatic segmentation method: 1) a deep neural network is trained to address the problem of vague organ boundaries in high class-imbalanced data. This network integrates a novel loss function to rigorously optimise boundary delineation using the modified Hausdorff metric and a sinusoidal component; 2) Given a test MRI volume, the output of the trained network predicts a sequence of targeted 2D pan- creas classes that are reconstructed as a volumetric binary mask. An energy-minimisation approach fuses a learned digital contrast model to suppress the intensities of non-pancreas classes, which, combined with the binary volume performs a refined segmentation in 3D while reveal- ing dense boundary detail. Experiments are performed on two diverse MRI datasets containing 180 and 120 scans, in which the proposed ap- proach achieves a mean Dice score of 84.1 ± 4.6% and 85.7 ± 2.3%, respectively. This approach is statistically stable and outperforms state- of-the-art methods on MRI

First Determination of the Weak Charge of the Proton

The Q(weak) experiment has measured the parity-violating asymmetry in (e) over right arrowp elastic scattering at Q(2) = 0.025 (GeV/c)(2), employing 145 mu A of 89% longitudinally polarized electrons on a 34.4 cm long liquid hydrogen target at Jefferson Lab. The results of the experiment\u27s commissioning run, constituting approximately 4% of the data collected in the experiment, are reported here. From these initial results, the measured asymmetry is A(ep) = -279 +/- 35 (stat) +/- 31 (syst) ppb, which is the smallest and most precise asymmetry ever measured in (e) over right arrowp scattering. The small Q(2) of this experiment has made possible the first determination of the weak charge of the proton Q(W)(p) by incorporating earlier parity-violating electron scattering (PVES) data at higher Q(2) to constrain hadronic corrections. The value of Q(W)(p) obtained in this way is Q(W)(p) (PVES) = 0.064 +/- 0.012, which is in good agreement with the standard model prediction of Q(W)(p) (SM) = 0.0710 +/- 0.0007. When this result is further combined with the Cs atomic parity violation (APV) measurement, significant constraints on the weak charges of the up and down quarks can also be extracted. That PVES + APV analysis reveals the neutron\u27s weak charge to be Q(W)(n) (PVES + APV) = -0.975 +/- 0.010

Polarization Analysis of p̄ Produced in pA Collisions

A quite simple procedure for the generation of a polarized antiproton beam could be worked out if antiprotons are produced with some polarization. In order to investigate this possibility measurements of the polarization of produced antiprotons have been started at a CERN/PS test beam. The polarization will be determined from the asymmetry of the elastic antiproton scattering at a liquid hydrogen target in the CNI region for which the analyzing power is well known. The data are under analysis and an additional measurement is done in 2018. Details on the experiment and the ongoing data analysis will be given

The proton and deuteron F_2 structure function at low Q^2

Measurements of the proton and deuteron $F_2$ structure functions are presented. The data, taken at Jefferson Lab Hall C, span the four-momentum transfer range $0.06 < Q^2 < 2.8$ GeV$^2$, and Bjorken $x$ values from 0.009 to 0.45, thus extending the knowledge of $F_2$ to low values of $Q^2$ at low $x$. Next-to-next-to-leading order calculations using recent parton distribution functions start to deviate from the data for $Q^2<2$ GeV$^2$ at the low and high $x$-values. Down to the lowest value of $Q^2$, the structure function is in good agreement with a parameterization of $F_2$ based on data that have been taken at much higher values of $Q^2$ or much lower values of $x$, and which is constrained by data at the photon point. The ratio of the deuteron and proton structure functions at low $x$ remains well described by a logarithmic dependence on $Q^2$ at low $Q^2$.Comment: 3 figures, submitted pape

Precision Electron-Beam Polarimetry using Compton Scattering at 1 GeV

We report on the highest precision yet achieved in the measurement of the polarization of a low energy, $\mathcal{O}$(1 GeV), electron beam, accomplished using a new polarimeter based on electron-photon scattering, in Hall~C at Jefferson Lab. A number of technical innovations were necessary, including a novel method for precise control of the laser polarization in a cavity and a novel diamond micro-strip detector which was able to capture most of the spectrum of scattered electrons. The data analysis technique exploited track finding, the high granularity of the detector and its large acceptance. The polarization of the $180~\mu$A, $1.16$~GeV electron beam was measured with a statistical precision of $<$~1\% per hour and a systematic uncertainty of 0.59\%. This exceeds the level of precision required by the \qweak experiment, a measurement of the vector weak charge of the proton. Proposed future low-energy experiments require polarization uncertainty $<$~0.4\%, and this result represents an important demonstration of that possibility. This measurement is also the first use of diamond detectors for particle tracking in an experiment.Comment: 9 pages, 7 figures, published in PR

Correlated Strength in Nuclear Spectral Function

We have carried out an (e,e'p) experiment at high momentum transfer and in parallel kinematics to measure the strength of the nuclear spectral function S(k,E) at high nucleon momenta k and large removal energies E. This strength is related to the presence of short-range and tensor correlations, and was known hitherto only indirectly and with considerable uncertainty from the lack of strength in the independent-particle region. This experiment confirms by direct measurement the correlated strength predicted by theory.Comment: 4 pages, 2 figures, accepted by Phys. Rev. Let