Elongation, flatness and compactness indices to characterise particle form

Angelidakis, Vasileios; Nadimi, Sadegh; Utili, Stefano

doi:10.1016/j.powtec.2021.11.027

Cited by 41 publications

(21 citation statements)

References 23 publications

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“…The average value of the elongation parameter of the observed kamacite particles is of about 0.4, corresponding to the ratio of principal ellipsoid axes of 2.5. Based on the calculated data, we can assume most particles have a “bladed” shape (Angelidakis et al., 2022), which is simply described as the elongated particles flattened along with one of the ellipsoidal axes.…”

Section: Resultsmentioning

confidence: 99%

The structural analysis of Kunya‐Urgench chondrite: The nondestructive neutron studies

Кичанов

Abdurakhimov

Zel

et al. 2022

Meteorit & Planetary Scien

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We present the results of neutron methods, specifically neutron diffraction and neutron tomography, in studying the structural organization of a Kunya‐Urgench chondrite fragment. The major phases of the meteorite fragment and variation of the phase content across the studied volume were revealed using neutron diffraction. The 3‐D model of the spatial distribution of metal and silicate phases inside the meteorite volume was obtained using neutron tomography. The distributions of volumes, average sizes, and shape‐related parameters of kamacite and silicate phases were analyzed. Shape preferred orientations of the kamacite particles were observed and the origins of shape fabric of these particles were discussed.

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Section: Resultsmentioning

confidence: 99%

The structural analysis of Kunya‐Urgench chondrite: The nondestructive neutron studies

Кичанов

Abdurakhimov

Zel

et al. 2022

Meteorit & Planetary Scien

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“…By definition AEL, AFL, and ACO have all values in (0, 1] and add up to unity [61]. Larger values of AEL, AFL, and ACO, respectively, indicate higher elongation, flatness, and compactness.…”

Section: Data Availability Statementmentioning

confidence: 99%

“…The objective of this study was to investigate one specific class of shape features, form factors, and, in particular, the potential of elongation, flatness, and compactness as recently defined in [61] to discriminate between benign and malignant lung lesions on CT scans. The main advantage of these parameters is that they have simple mathematical definitions and relatively easy/intuitive interpretation, as they can be seen as percentages of an overall form, respectively elongated (rod-like), flat (platy), and compact (equant).…”

Section: Introductionmentioning

confidence: 99%

Form Factors as Potential Imaging Biomarkers to Differentiate Benign vs. Malignant Lung Lesions on CT Scans

Bianconi

Palumbo

Fravolini

et al. 2022

Sensors

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Indeterminate lung nodules detected on CT scans are common findings in clinical practice. Their correct assessment is critical, as early diagnosis of malignancy is crucial to maximise the treatment outcome. In this work, we evaluated the role of form factors as imaging biomarkers to differentiate benign vs. malignant lung lesions on CT scans. We tested a total of three conventional imaging features, six form factors, and two shape features for significant differences between benign and malignant lung lesions on CT scans. The study population consisted of 192 lung nodules from two independent datasets, containing 109 (38 benign, 71 malignant) and 83 (42 benign, 41 malignant) lung lesions, respectively. The standard of reference was either histological evaluation or stability on radiological followup. The statistical significance was determined via the Mann–Whitney U nonparametric test, and the ability of the form factors to discriminate a benign vs. a malignant lesion was assessed through multivariate prediction models based on Support Vector Machines. The univariate analysis returned four form factors (Angelidakis compactness and flatness, Kong flatness, and maximum projection sphericity) that were significantly different between the benign and malignant group in both datasets. In particular, we found that the benign lesions were on average flatter than the malignant ones; conversely, the malignant ones were on average more compact (isotropic) than the benign ones. The multivariate prediction models showed that adding form factors to conventional imaging features improved the prediction accuracy by up to 14.5 pp. We conclude that form factors evaluated on lung nodules on CT scans can improve the differential diagnosis between benign and malignant lesions.

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Section: Shape Parameter Formula Commentsmentioning

confidence: 99%

“…Zingg [20] proposed an intuitive visualization of particle form, plotting two aspect ratios c/b against b/a, in what is widely referred to as a Zingg plot, where a > b > c the main particle dimensions. Angelidakis et al [19] recently proposed a new classification system for particle form, which they plotted on top of a Zingg plot.…”

Section: Shape Characteristics Of Iron Pyritementioning

confidence: 99%

Nano‐Scale Characterization of Particulate Iron Pyrite Morphology in Shale

Angelidakis

Nadimi

Garum

et al. 2022

Part & Part Syst Charact

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This study analyses the morphology of iron pyrite particles within a shale sample, captured using nano-computed tomography (Nano-CT). The complex, framboidal morphology of the iron pyrite particles is characterised using various metrics, and comparisons are drawn on their effectiveness to quantify their observed morphological characteristics. Then, simplified representations of selected iron pyrite particles are generated to facilitate a sensitivity analysis of the effect of imaging resolution on morphological parameters of particle form. A discussion is developed on the required number of pixels per particle diameter for particle shape characterisation. It is shown that shape indices that rely on the simplified main particle dimensions can be accurately calculated even for low fidelity levels of 10 pixels per particle diameter. More complex shape indices, that use vertices, volume and surface area, are more sensitive to image resolution even for 40 pixels per particle diameter.

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Elongation, flatness and compactness indices to characterise particle form

Cited by 41 publications

References 23 publications

The structural analysis of Kunya‐Urgench chondrite: The nondestructive neutron studies

The structural analysis of Kunya‐Urgench chondrite: The nondestructive neutron studies

Form Factors as Potential Imaging Biomarkers to Differentiate Benign vs. Malignant Lung Lesions on CT Scans

Nano‐Scale Characterization of Particulate Iron Pyrite Morphology in Shale

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