Shape from Projections via Differentiable Forward Projector for Computed Tomography

In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data

Three Dimensional Polarimetric Neutron Tomography of Magnetic Fields

Through the use of Time-of-Flight Three Dimensional Polarimetric Neutron Tomography (ToF 3DPNT) we have for the first time successfully demonstrated a technique capable of measuring and reconstructing three dimensional magnetic field strengths and directions unobtrusively and non-destructively with the potential to probe the interior of bulk samples which is not amenable otherwise. Using a pioneering polarimetric set-up for ToF neutron instrumentation in combination with a newly developed tailored reconstruction algorithm, the magnetic field generated by a current carrying solenoid has been measured and reconstructed, thereby providing the proof-of-principle of a technique able to reveal hitherto unobtainable information on the magnetic fields in the bulk of materials and devices, due to a high degree of penetration into many materials, including metals, and the sensitivity of neutron polarisation to magnetic fields. The technique puts the potential of the ToF time structure of pulsed neutron sources to full use in order to optimise the recorded information quality and reduce measurement time.Comment: 12 pages, 4 figure

Genetic diversity of the NE Atlantic sea urchin Strongylocentrotus droebachiensis unveils chaotic genetic patchiness possibly linked to local selective pressure

We compared the genetic differentiation in the green sea urchin Strongylocentrotus droebachiensis from discrete populations on the NE Atlantic coast. By using eight recently developed microsatellite markers, genetic structure was compared between populations from the Danish Strait in the south to the Barents Sea in the north (56–79°N). Urchins are spread by pelagic larvae and may be transported long distances by northwards-going ocean currents. Two main superimposed patterns were identified. The first showed a subtle but significant genetic differentiation from the southernmost to the northernmost of the studied populations and could be explained by an isolation by distance model. The second pattern included two coastal populations in mid-Norway (65°N), NH and NS, as well as the northernmost population of continental Norway (71°N) FV. They showed a high degree of differentiation from all other populations. The explanation to the second pattern is most likely chaotic genetic patchiness caused by introgression from another species, S. pallidus, into S. droebachiensis resulting from selective pressure. Ongoing sea urchin collapse and kelp forests recovery are observed in the area of NH, NS and FV populations. High gene flow between populations spanning more than 22° in latitude suggests a high risk of new grazing events to occur rapidly in the future if conditions for sea urchins are favourable. On the other hand, the possibility of hybridization in association with collapsing populations may be used as an early warning indicator for monitoring purposes.publishedVersio

Melt in the Greenland EastGRIP ice core reveals Holocene warm events

We present a record of melt events obtained from the East Greenland Ice Core Project (EastGRIP) ice core in central northeastern Greenland, covering the largest part of the Holocene. The data were acquired visually using an optical dark-field line scanner. We detect and describe melt layers and lenses, seen as bubble-free layers and lenses, throughout the ice above the bubble–clathrate transition. This transition is located at 1150 m depth in the EastGRIP ice core, corresponding to an age of 9720 years b2k. We define the brittle zone in the EastGRIP ice core as that from 650 to 950 m depth, where we count on average more than three core breaks per meter. We analyze melt layer thicknesses, correct for ice thinning, and account for missing layers due to core breaks. Our record of melt events shows a large, distinct peak around 1014 years b2k (986 CE) and a broad peak around 7000 years b2k, corresponding to the Holocene Climatic Optimum. In total, we can identify approximately 831 mm of melt (corrected for thinning) over the past 10 000 years. We find that the melt event from 986 CE is most likely a large rain event similar to that from 2012 CE, and that these two events are unprecedented throughout the Holocene. We also compare the most recent 2500 years to a tree ring composite and find an overlap between melt events and tree ring anomalies indicating warm summers. Considering the ice dynamics of the EastGRIP site resulting from the flow of the Northeast Greenland Ice Stream (NEGIS), we find that summer temperatures must have been at least 3 ± 0.6 ∘C warmer during the Early Holocene compared to today

Prevalence of Epithelial Ovarian Cancer Stem Cells Correlates with Recurrence in Early-Stage Ovarian Cancer

Epithelial ovarian cancer stem cells (EOC stem cells) have been associated with recurrence and chemoresistance. CD44 and CK18 are highly expressed in cancer stem cells and function as tools for their identification and characterization. We investigated the association between the number of CD44+ EOC stem cells in ovarian cancer tumors and progression-free survival. EOC stem cells exist as clusters located close to the stroma forming the cancer stem cell “niche”. 17.1% of the samples reveled high number of CD44+ EOC stem cells (>20% positive cells). In addition, the number of CD44+ EOC stem cells was significantly higher in patients with early-stage ovarian cancer (FIGO I/II), and it was associated with shorter progression-free survival (P = 0.026). This study suggests that quantification of the number of EOC stem cells in the tumor can be used as a predictor of disease and could be applied for treatment selection in early-stage ovarian cancer

Large-scale data for multiple-view stereopsis

The seminal multiple-view stereo benchmark evaluations from Middlebury and by Strecha et al. have played a major role in propelling the development of multi-view stereopsis (MVS) methodology. The somewhat small size and variability of these data sets, however, limit their scope and the conclusions that can be derived from them. To facilitate further development within MVS, we here present a new and varied data set consisting of 80 scenes, seen from 49 or 64 accurate camera positions. This is accompanied by accurate structured light scans for reference and evaluation. In addition all images are taken under seven different lighting conditions. As a benchmark and to validate the use of our data set for obtaining reasonable and statistically significant findings about MVS, we have applied the three state-of-the-art MVS algorithms by Campbell et al., Furukawa et al., and Tola et al. to the data set. To do this we have extended the evaluation protocol from the Middlebury evaluation, necessitated by the more complex geometry of some of our scenes. The data set and accompanying evaluation framework are made freely available online. Based on this evaluation, we are able to observe several characteristics of state-of-the-art MVS, e.g. that there is a tradeoff between the quality of the reconstructed 3D points (accuracy) and how much of an object’s surface is captured (completeness). Also, several issues that we hypothesized would challenge MVS, such as specularities and changing lighting conditions did not pose serious problems. Our study finds that the two most pressing issues for MVS are lack of texture and meshing (forming 3D points into closed triangulated surfaces)

Assessment of algorithms for mitosis detection in breast cancer histopathology images

The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers. However, mitosis counting is laborious, subjective and may suffer from low inter-observer agreement. With the wider acceptance of whole slide images in pathology labs, automatic image analysis has been proposed as a potential solution for these issues. In this paper, the results from the Assessment of Mitosis Detection Algorithms 2013 (AMIDA13) challenge are described. The challenge was based on a data set consisting of 12 training and 11 testing subjects, with more than one thousand annotated mitotic figures by multiple observers. Short descriptions and results from the evaluation of eleven methods are presented. The top performing method has an error rate that is comparable to the inter-observer agreement among pathologists