29,938 research outputs found
Automatic quantification of the microvascular density on whole slide images, applied to paediatric brain tumours
Angiogenesis is a key phenomenon for tumour progression, diagnosis and
treatment in brain tumours and more generally in oncology. Presently, its
precise, direct quantitative assessment can only be done on whole tissue
sections immunostained to reveal vascular endothelial cells. But this is a
tremendous task for the pathologist and a challenge for the computer since
digitised whole tissue sections, whole slide images (WSI), contain typically
around ten gigapixels.
We define and implement an algorithm that determines automatically, on a WSI
at objective magnification , the regions of tissue, the regions
without blur and the regions of large puddles of red blood cells, and
constructs the mask of blur-free, significant tissue on the WSI. Then it
calibrates automatically the optical density ratios of the immunostaining of
the vessel walls and of the counterstaining, performs a colour deconvolution
inside the regions of blur-free tissue, and finds the vessel walls inside these
regions by selecting, on the image resulting from the colour deconvolution,
zones which satisfy a double-threshold criterion. A mask of vessel wall regions
on the WSI is produced. The density of microvessels is finally computed as the
fraction of the area of significant tissue which is occupied by vessel walls.
We apply this algorithm to a set of 186 WSI of paediatric brain tumours from
World Health Organisation grades I to IV. The segmentations are of very good
quality although the set of slides is very heterogeneous. The computation time
is of the order of a fraction of an hour for each WSI on a modest computer. The
computed microvascular density is found to be robust and strongly correlates
with the tumour grade.
This method requires no training and can easily be applied to other tumour
types and other stainings
An automated pattern recognition system for the quantification of inflammatory cells in hepatitis-C-infected liver biopsies
This paper presents an automated system for the quantification of inflammatory cells in hepatitis-C-infected liver biopsies. Initially, features are extracted from colour-corrected biopsy images at positions of interest identified by adaptive thresholding and clump decomposition. A sequential floating search method and principal component analysis are used to reduce dimensionality. Manually annotated training images allow supervised training. The performance of Gaussian parametric and mixture models is compared when used to classify regions as either inflammatory or healthy. The system is optimized using a response surface method that maximises the area under the receiver operating characteristic curve. This system is then tested on images previously ranked by a number of observers with varying levels of expertise. These results are compared to the automated system using Spearman rank correlation. Results show that this system can rank 15 test images, with varying degrees of inflammation, in strong agreement with five expert pathologists
Quantitative characterization of pore structure of several biochars with 3D imaging
Pore space characteristics of biochars may vary depending on the used raw
material and processing technology. Pore structure has significant effects on
the water retention properties of biochar amended soils. In this work, several
biochars were characterized with three-dimensional imaging and image analysis.
X-ray computed microtomography was used to image biochars at resolution of 1.14
m and the obtained images were analysed for porosity, pore-size
distribution, specific surface area and structural anisotropy. In addition,
random walk simulations were used to relate structural anisotropy to diffusive
transport. Image analysis showed that considerable part of the biochar volume
consist of pores in size range relevant to hydrological processes and storage
of plant available water. Porosity and pore-size distribution were found to
depend on the biochar type and the structural anisotopy analysis showed that
used raw material considerably affects the pore characteristics at micrometre
scale. Therefore attention should be paid to raw material selection and quality
in applications requiring optimized pore structure.Comment: 16 pages, 4 figures. The final publication is available at Springer
via http://dx.doi.org/10.1007/s11356-017-8823-
A 4-D dataset for validation of crystal growth in a complex three-phase material, ice cream
Four dimensional (4D, or 3D plus time) X-ray tomographic imaging of phase changes in materials is quickly becoming an accepted tool for quantifying the development of microstructures to both inform and validate models. However, most of the systems studied have been relatively simple binary compositions with only two phases. In this study we present a quantitative dataset of the phase evolution in a complex three-phase material, ice cream. The microstructure of ice cream is an important parameter in terms of sensorial perception, and therefore quantification and modelling of the evolution of the microstructure with time and temperature is key to understanding its fabrication and storage. The microstructure consists of three phases, air cells, ice crystals, and unfrozen matrix. We perform in situ synchrotron X-ray imaging of ice cream samples using in-line phase contrast tomography, housed within a purpose built cold-stage (-40 to +20oC) with finely controlled variation in specimen temperature. The size and distribution of ice crystals and air cells during programmed temperature cycling are determined using 3D quantification. The microstructural evolution of three-phase materials has many other important applications ranging from biological to structural and functional material, hence this dataset can act as a validation case for numerical investigations on faceted and non-faceted crystal growth in a range of materials
Latest developments in 3D analysis of geomaterials by Morpho+
At the Centre for X-ray Tomography of the Ghent University (Belgium) (www.ugct.ugent.be) besides hardware development for high-resolution X-ray CT scanners, a lot of progress is being made in the field of 3D analysis of the scanned samples. Morpho+ is a flexible 3D analysis software which provides the necessary petrophysical parameters of the scanned samples in 3D. Although Morpho+ was originally designed to provide any kind of 3D parameter, it contains some specific features especially designed for the analysis of geomaterial properties like porosity, partial porosity, pore-size distribution, grain size, grain orientation and surface determination. Additionally, the results of the 3D analysis can be visualized which enables to understand and interpret the analysis results in a straightforward way. The complementarities between high-quality X-ray CT images and flexible 3D software are opening up new gateways in the study of geomaterials
Automated Assessment of Facial Wrinkling: a case study on the effect of smoking
Facial wrinkle is one of the most prominent biological changes that
accompanying the natural aging process. However, there are some external
factors contributing to premature wrinkles development, such as sun exposure
and smoking. Clinical studies have shown that heavy smoking causes premature
wrinkles development. However, there is no computerised system that can
automatically assess the facial wrinkles on the whole face. This study
investigates the effect of smoking on facial wrinkling using a social habit
face dataset and an automated computerised computer vision algorithm. The
wrinkles pattern represented in the intensity of 0-255 was first extracted
using a modified Hybrid Hessian Filter. The face was divided into ten
predefined regions, where the wrinkles in each region was extracted. Then the
statistical analysis was performed to analyse which region is effected mainly
by smoking. The result showed that the density of wrinkles for smokers in two
regions around the mouth was significantly higher than the non-smokers, at
p-value of 0.05. Other regions are inconclusive due to lack of large scale
dataset. Finally, the wrinkle was visually compared between smoker and
non-smoker faces by generating a generic 3D face model.Comment: 6 pages, 8 figures, Accepted in 2017 IEEE SMC International
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