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Tecniche di imaging con luce di sincrotrone per lo

studio dei geomateriali: dalla radiografia alla

tomografia computerizzata a 4 dimensioni

Lucia MANCINI

Elettra - Sincrotrone Trieste S.C.p.A.

34149 Basovizza (Trieste) – Italy

The Synchrotron Light

The electromagnetic radiation generated by charged particles, typically electrons

or positrons, traveling through magnetic fields at speed very close to the speed of

light. The frequencies generated can range over the entire electromagnetic

spectrum.

Beamline

Beamline

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SYRMEP: the imaging beamline @ Elettra

Designed and constructed in collaboration with the Trieste section of INFN

and the Physics Dept. of Università di Trieste. Devoted to the development

and application of hard X-ray imaging techniques.

Medical applications

- in vitro and ex-vivo experiments bones, tissues, teeth, drugs, ...

-in-vivo studies small animals

mammography

Material science studies

- microstructural features in a very large range of materials

- purpose relationships with physical properties

The SYRMEP beamline @ Elettra

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Elettra b e n d i n g

m a g n e t

i o n i z a t i o n c h a m b e r

s a m p l e

v a c u u m s l i ts

detector

double Si(111)

monochromator

air slits

stage

The SYRMEP beamline layout

Energy range: 8.3 38 keV, Bandwidth E/E 2x10-3

Beam size at sample (h x v) 160 mm x 5-6 mm

Source size (FWHM) s (h x v) 230 mm x 80 mm

Typical fluxes @15 keV 7 * 108 phot./mm2 s (@ 2.4 GeV, 180 mA)

Source-to-sample distance: D 23 m

Why hard X-ray imaging at a 3rd generation SR facility?

high energy photons and high flux

heavy and/or bulky samples in transmission geometry

tunability in a large energy range (optimization, artefacts - dose reduction)

short exposure times (scan duration, real time)

small angular source size and big source-to-sample distance

high spatial resolution (r = s d / D < 1 mm @ SYRMEP)

possibility of big sample-to-detector distances (d < 1 m)

high spatial coherence of the X beam (Lc = l D/(2 s) 10 µm @15keV)

Phase-sensitive techniques

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Absorption and Phase-Contrast radiography

Refractive index: n = 1 - i

sample

d

detector

d 0.11 m

Synchrotron

source

D

detector

d 0

(P. Cloetens, ESRF

France)

Phase contrast: due to refraction of X-rays

in the object

Absorption contrast: due to differences in

absorption of X–rays in the object

Fresnel diffraction

n = 1 - - i : refraction index

PC Regimes

Free-space propagation

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Phase vs. Amplitude effects with hard X-rays

Phase-contrast could be observed also when absorption-contrast undetectable

Gain up to a few 1000!

(by P. Cloetens, ESRF, France)

@ 25 keV

Absorption image Phase-contrast image

@ 10 keV

Absorption image

Images of a Mimosa flower (D. Dreossi & co.)

Phase-contrast image

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Radiographs of an AlPdMn grain recorded at the ESRF (France)

Absorption radiograph

Phase radiograph

Mancini L., PhD Thesis, 1998

Mancini L. et al., Phil. Mag. A 78 (1998) 1175

200 mm

lamellae

holes

E = 35.5 keV

~3 cm

Lezard

E = 17 keV

d = 50 cm

Courtesy of A. Astolfo SYRMEP

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Synchrotron X-ray computed microtomography (m -CT)

PC

Sample

Scintillator Screen

CCD camera

White or monochromatic X-ray beam

y

x

z

d

q

Planar Radiographs Sample Stage

Precious for investigation of internal features without sample sectioning:

in many cases the sectioning procedure modifies the sample structure

the sample can be after studied by other experimental techniques,

or submitted to several treatments (mechanical, thermal, etc...)

SYRMEP: mCT setup, detectors & optics

Photonic Science HYSTAR

16 bit, 2048 x 2048 pixels2

pixel size: (3.85) 14 x (3.85) 14 mm2

FOV: (8) 28 mm x (8) 28 mm

Photonic Science VHR

12 bit, 4008 x 2672 pixels2

effective pixel size: 4.5x4.5 mm2

FOV: 18 mm x 12 mm

Photonic Science Lens-coupled

16 bit, 2048 x 2048 pixels2

pixel size: 7.4x7.4 mm2

FOV: continuously adjustable

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TOMOLAB

Designed at Elettra and constructed in

collaboration with Dip. Ingegneria e

Architettura and Corso di Laurea in

Odontoiatria e Protesi Dentaria of the

Università of Trieste.

Source: V = 40÷130 kV, Pmax = 39 W,

focal spotmin = 5 mm

CCD camera: 12bit, pixel size = 12.5 µm,

FOVma= 50 mm x 33 mm

TomoLab: a cone-beam m-CT station @Elettra

Inside the facility

X-ray

sourc

e

Flat

panel

detect

or

Sample stage

Source: V = 40÷150 kV, Pmax=

75 W, focal spotmin = 5 mm

Detector: 12bit, pixel size = 50

µm, FOVma= 120 mm x 120 mm

C. Tuniz et al., NIM A , 711 (2013) 106-110

The ICTP-Elettra X-ray laboratory for

cultural heritage, archaeology and paleontology

Coordinator: Prof. Claudio Tuniz

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Elaboration of tomographic images

Planar radiographs are elaborated by a reconstruction procedure

Reconstructed slices are then visualized:

2D slices visualized as Stack

3D views of the sample can be obtained (Volume rendering)

Courtesy of S. Favretto

Lezard

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Aim: In vivo mammography studies on cases selected by Radiologist

Target: dense breasts;

conventional radiographs with uncertain diagnosis.

Dose reduction

Improvement of the contrast resolution

Agreement among the Public Hospital of Trieste, the University of Trieste and Elettra

Breast imaging: the SYRMA (SYnchrotron

Radiation for MAmmography) project

{Financed by Fondazione Cassa di Risparmio di Trieste}

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Phase-contrast

radiography

Tesei L. et al., Nucl. Instrum. and Meth. A, 548 (2005) 257-263

E = 29 keV, d = 17 cm

Implanted bone

Biomaterials

1 mm

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2 mm

Food science

1 mm Voxel=(8x6.78x2.8) mm3

E = 13 keV

d = 6 cm

P.M. Falcone et al., Journal of Food Science 69 (2004) E39-E43

P.M. Falcone et al., Advances in Food and Nutrition Research 51 (2006), 205-263

Aerated chocolate Bread crumb

E = 12 keV

d = 20 cm

Polymeric foams Wood

Soft matter

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Non-destructive evaluation of ancient

musical instruments

Heat transfer in Aluminum metal foams

STL modeling and Computational Fluid Dynamics simulations

P. Ranut , E. Nobile, L. Mancini, Experimental Thermal and Fluid Science (2015)

30 PPI 20 PPI 10 PPI

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M. Galiová, J. Kaiser et al., Analytical and Bioanalytical Chemistry, 398 (2010) 1095

Paleontology

Pathological fossil snake vertebra (1 Ma. old)

1 mm

1 mm

Bee trapped in Amber 20-40 Ma. old found

in the Dominican Republic

Greco M.K. et al., Insectes Sociaux, 8 (2011) 1-8

Swiss Bee Research Centre

1 mm

E = 14 keV

d = 20 cm

# of proj. = 900

Sagittal view of Proplebeia abdita

(Greco and Engel n. sp. holotype)

CB: central body of brain

RT: retinal zone of compound eyes

DM: direct flight muscles

IM: indirect flight muscles

RM: loaded rectum

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N. Marinoni et al., Journal of Material Science, 44 (2009) 5815-5823.

J. Kaiser et al., Urological Research, (2010), in press.

Cement-based materials

Human kidney stones

Multi-phase systems

The Pore3D project: why?

A sw library specifically designed for X-ray μ-CT images of porous media

and multiphase systems, Manipulation of huge datasets with common hw.

Different strategies of analysis as a function of the scientific application:

Pore3D implements several algorithms for each step of the analysis, having

a full control of the parameters of the algorithm and of the intermediate

results.

On the basis of specific know-how of the SYRMEP collaboration the main

aim was to merge many of features implemented in existing software, in some

cases customizing it or adding new tools.

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Pore3D is a tool for 3D image processing and analysis

http://www.elettra.eu/pore3d

Filters

Basic (mean, median, gaussian, ...)

Anisotropic diffusion

Bilateral

Ring artifacts reduction

Binary (median, clear border, ...)

Segmentation

Automatic thresholding (Otsu, Kittler, ...)

Adaptive thresholding

Region growing

Multiphase thresholding

Clustering (k-means, k-medians, ...)

Morphological processing

Dilation and erosion

Morphological reconstruction

Watershed segmentation

Distance transform

H-Minima filter

Skeleton extraction

Thinning

Medial axis (LKC)

DOHT

Gradient Vector Flow

Skeleton pruning

Skeleton labeling

Analysis

Minkowski functionals

Morphometric analysis

Anisotropy analysis

Blob analysis

Skeleton analysis

Textural analysis (fractal

dimension, ...)

F. Brun et al., NIM A, 615 (2010) 326–332

The Pore3D software library @ Elettra

S. Puce et al., Zoomorphology, 130 (2011) 85-95

3D rendering of a branch

3D analysis of the canal network of Stylaster sp.

(Cnidaria, Hydrozoa) by means of X-ray mCT

Colony in situ

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DACTYLOPORE

Section of a branch without coenostem

AMPULLAE

THIN CANALS

GASTROPORE

TomoLab

Analysis of coral’s transverse sections sequence shows:

reciprocal relationship between adjacent cyclosystems

each new cyclosystem buds between gastropore and dactylopores of last formed one

Old and new gastropores

surrounded by a single ring

of dactylopores

Cyclosystem Cyclosystem enlargement Cyclosystems completely

separated

Study of the growth process

S. Puce et al., Coral Reefs, 31 (2012) 715-730

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m-CT imaging of multiphase flow in carbonates (core 5 mm)

M.J. Blunt et al., Advances in Water Resources, 51 (2013) 197-216.

S. Iglauer et al., Fuel, 103 (2013) 905-914.

Portland limestone Indiana limestone Guilting limestone

Middle Eastern carbonates Mount Gambier limestone

Clashach sandstone: oil-water distribution

3D distribution of brine (blue) and residual oil clusters (red)

voxel size: 9 mm

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3D quantitative analysis of igneous rocks Formation of a volcanic rock: a

complex process with many steps

involved, from magma ascent in the

conduit to fragmentation and

emplacement beyond the crater's rim.

Products of explosive eruptions, such

as pumices and scoriae, feature an

arrangement of crystals and vesicles

within a glassy matrix. This

represents the status of the magma

prior to the fragmentation process;

then a great deal of information about

the history of the rock formation can

be obtained by the study of its

morphology and texture.

Courtesy of M. Polacci (INGV, Pisa)

SYRMEP

D.R. Baker, L. Mancini et al., Lithos, 148 (2012) 262-276 Sagittal and frontal slices

pixel size = 9 μm

E = 28 keV

mCT images of a pumice rock from Ambrym volcano

@ SYRMEP

Axial view

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D.R. Baker, L. Mancini et al., Lithos, 148 (2012) 262-276

3D movie of a pumice rock from Ambrym volcano

Scoria from Ambrym, moderately vesiculated, poorly crystallized

Abundance of isolated vesicles

Connected component analysis

Red: connected component

Yellow: the others

Vesicles isolated after watershed

segmentation and border

cleaning.

Vesicles -> 50 %

D. Zandomeneghi et al., Geosphere, 6 (2010) 793-804

Scoria from Stromboli, poorly to moderately vesiculated, highly crystallized

Blue: pyroxene crystals

Yellow: feldspar crystals

vesicles -> 36 %

pyroxenes -> 28%

feldspars -> 12%,

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M. Voltolini et al., J. of Volc. and Geothermal Res., 202 (2011) 83-95

Scoria from Etna (experiments performed at the TOMCAT

beamline at the Swiss Synchrotron Light Source, PSI)

oxides

feldspars pyroxenes

vesicles -> 68.9%, plagioclases -> 4.3%, pyroxenes -> 3.2%, “oxides” -> 0.7%, glass -> 22.9%. vesicles -> 68.9%, plagioclases -> 4.3%, pyroxenes -> 3.2%, “oxides” -> 0.7%, glass -> 22.9%

voxel size: 1.85 μm

But …. more complicated samples

A synthetic trachyte sample obtained by crystallization experiments (under

controlled conditions of pressure, temperature and time) in water-saturated

conditions starting from material of Campi Flegrei (Italy). Small crystals of

alkali feldspars embedded in a glass matrix: one of the most complicated

cases to perform image segmentation because of their similar density and

chemical composition.

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The phase-retrieval

approach

Phase retrieval

Back projection

Computed tomography

reconstruction

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Synthetic trachyte sample (material from Campi Flegrei)

Reconstructed axial slice

after phase-retrieval Reconstructed axial slice

F. Arzilli, L. Mancini, et al., Lithos, 216-217 (2015) 93-105

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F. Arzilli, L. Mancini et al., Lithos, 216-217 (2015) 93-105

3D segmentation and separation of alkali-feldspar spherulites

3D visualization of a alkali-feldspar spherulite

F. Arzilli, L. Mancini et al., Lithos, 216-217 (2015) 93-105

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In the Pole Figures the long,

medium and short axes of

the ellipsoids used for fitting

the single lamella are

plotted.

3D Shape Preferred Orientation (SPO) analyses

F. Arzilli et al., Lithos, 216-217 (2015) 93-105

A 4D X-ray tomographic microscopy study of

bubble growth in basaltic foam

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TOMCAT beamline at the Swiss Light Source (Villigen)

Sample spindle

Laser

Microscope

and CMOS

camera

D.R. Baker et al., Nature Communications, 3 (2012) 1135

4D movie of the bubble growth

Hydrated glasses (3 and 7 wt.%

H2O content) heated by a laser

furnace to above glass transition,

~600°C, in < 30 s.

As T increased to ~1200°C, full

3D data sets collected every

second for 18 s.

Rapidity of heating simulates

instantaneous decompression.

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Skeletonization to measure bubble and pore throat sizes

in a volcanic rock ((3 wt.% of dissolved H2O)

a) Topology preserving skeleton with nodes (red) at the intersections of the branches

(yellow).

b) Maximal inscribed spheres to calculate bubble volumes.

c) Maximal inscribed spheres to calculate pore throat diameters and wall thicknesses.

a) b) c)

D.R. Baker et al., Nature Communications, 3 (2012) 1135

Experiments vs. natural Bubble Size Distributions

Polacci et al., J. of Geophysical Research, 114 (2009) B01206

Normal Strombolian eruption Paroxysmal eruption

4D experiments

D.R. Baker et al., Nature

Comm., 3 (2012) 1135

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Conclusions

Many topics in petrology, volcanology, structural geology,

sedimentology and paleontology can be afforded by using 3D-4D CT

imaging combined with quantitative image analysis and complementary

techniques (electron and X-ray micro-analysis, neutron imaging and

diffraction, ….)

Spatial

resolution Sample size/

material

Beamtime

availability

Info

to extract

Sample

damage

Vi aspettiamo @ Elettra!

Grazie per l’attenzione

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A. Abrami, F. Arzilli, F. Brun, K. Casarin, V. Chenda, A. Curri, D. Dreossi, C. Fava, G. Kourousias, E. Larsson, S. Mohammadi, R.H. Menk, R. Pugliese, N. Sodini, G. Tromba, A. Vascotto, F. Zanini (Elettra – Sincrotrone Trieste , Italy)

F. Arfelli, M. Biasotto, E. Castelli, R. di Lenarda, R. Longo, E. Nobile, P. Ranut, L. Rigon, G. Schena, G. Turco (Università di Trieste)

M. Polacci, P. Landi (INGV Pisa, Italy), D. Giordano (Univ. of Torino, Italy)

M. Rivers (CARS, Univ. of Chicago, USA)

D.R. Baker, A. La Rue, C. O'Shaughnessy (McGill Univ. of Montréal, Canada)

D. Morgavi, D. Perugini (Univ. of Perugia, Italy)

M. Voltolini (Lawrence Berkeley National Lab., California, USA)

D.B. Dingwell (LMU – Munich, Germany)

A. Bernasconi, N.. Marinoni, A. Pavese, P. Vignola (Univ. of Milano, Italy)

J. L. Fife, F. Marone (SLS, Villigen, Switzerland)

C. Pritchard, P. Larson (Washington University, USA)

F. Bernardini, M.L. Crespo, C. Tuniz, C. Zanolli (ICTP, Trieste)

L. Bondioli, A. Coppa, R. Macchiarelli (Univ. Roma, Univ. Poitiers)

G. Bavestrello, D. Pica, S. Puce (Università di Ancona, Italy)

M. Galiová, M. Holá, J. Kaiser (Brno Univ. of Technology, Czech Republic

E grazie a ….