scholarly journals Morphometric Parameters of Krumbein Grain Shape Charts—A Critical Approach in Light of the Automatic Grain Shape Image Analysis

Minerals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 937
Author(s):  
Jacek Bogusław Szmańda ◽  
Karol Witkowski

Grain-shape analyses are essential in geological research because they provide the basis for genetic interpretations, including sedimentation conditions. The methods of visual evaluation used so far have been subjective, time-consuming and labour intensive. Automatic particle image analysis, including the methods used by the Morphology G3SE device, open up the possibility of mass and objective roundness analysis of mineral and organic particles. The article presents the results of measurements for the grain scale proposed by Krumbein in 1941, as this scale has been used in numerous sedimentological studies. The standard shapes were analysed using four parameters: High Sensitivity (HS) Circularity, Convexity, Solidity and Aspect Ratio. In the discussion, both the results and the grain-shape standards were critically assessed. The most important trends in the distribution of morphometric parameters of the scale are shown. On this basis, it was found that it is impossible to determine the parameter boundary values that would distinguish each class of grain roundness proposed by Krumbein. The conclusions propose criteria for the automatic differentiation of angular, subrounded and rounded grains, which could be a basis for describing the shape of mineral particles.

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Marie Luby ◽  
Jennifer Hong ◽  
José G Merino ◽  
John K Lynch ◽  
Amie W Hsia ◽  
...  

Objectives: In the clinical setting, the extent of mismatch on MRI is frequently assessed with an approximate “XYZ/2” method but the agreement with the “gold standard” planimetric volume and the “visual evaluation” methods are not known. In a published study, we established that the visual evaluation and planimetric methods are equivalent as far as mismatch classification. The objectives of this study were to quantify the agreement of the approximate method with the “gold standard” and “visual evaluation” methods and to compare the mismatch classification results. Methods: Patients were selected from the Lesion Evolution of Stroke and Ischemia On Neuroimaging (LESION) database if they: had an acute ischemic stroke, were treated with intravenous rt-PA only, and had a pre-treatment MRI with evaluable maps including trace or isotropic b1000 DWI and MTT images. A trained rater viewed the images on the PACS, placed the two perpendicular linear measurements, “X” and “Y”, on the slices with the largest DWI and MTT lesion areas, and then used a “XYZ/2” formula where “Z” was the product of the slice thickness and the total number of slices containing the lesion. A separate expert rater measured the planimetric volumes on a slice-by-slice basis with a semiautomated segmentation tool followed by manual editing. Expert readers evaluated the MRI scans for the presence of qualitative mismatch. The expert readers were not the trained reader that performed the approximate volume measurements. Quantitative mismatch was considered present if MTT volume - DWI volume ≥50 ml. Mismatch classifications using the ≥ 50 ml definition were compared by constructing contingency tables. Results: A total of 194 patients met the study criteria and had median DWI and MTT planimetric volumes of 13.06 ml and 99.27 ml respectively. For both the DWI (n=170) and MTT (n=164), 94% of the measurements were within two standard deviations of the difference between the planimetric and approximate volume measurements. Comparing the planimetric and approximate volume measurements, the Spearman correlation coefficients were 0.855 and 0.886 for the DWI and MTT measurements respectively (p<0.01). Compared to the planimetric method, the approximate “XYZ/2” method had a high sensitivity (0.91), specificity (0.80), accuracy (0.86) and positive predictive value (0.85) to detect mismatch using the ≥ 50 ml definition. Compared to the qualitative method, the approximate “XYZ/2” method had a sensitivity (0.77), specificity (0.76), accuracy (0.77) and positive predictive value (0.87) to detect mismatch using the ≥ 50 ml definition. Conclusions: The approximate “XYZ/2” method is sufficient for classifying the presence of MRI determined mismatch in acute stroke patients and therefore is a potential tool when using MRI determined mismatch as an inclusion criteria for clinical trials.


1998 ◽  
Vol 167 ◽  
pp. 163-170
Author(s):  
Yutaka Uchida

AbstractWe describe in this paper some of the findings of the Yohkoh satellite about the coronal structure surrounding dark filaments in the pre-event and initial phases of high latitude arcade formation events. The knowledge of pre-event structure and its change is essential for the proper understanding of the arcade flaring process from the causality point of view. The wide dynamic range and high sensitivity obervations by Yohkoh allow us to look into the faint structures and their changes with the use of a faint-feature-enhancing technique in the image analysis.


Acta Numerica ◽  
1994 ◽  
Vol 3 ◽  
pp. 1-59 ◽  
Author(s):  
Luis Alvarez ◽  
Jean Michel Morel

In this article we shall present a unified and axiomatized view of several theories and algorithms of image multiscale analysis (and low level vision) which have been developed in the past twenty years. We shall show that under reasonable invariance and assumptions, all image (and shape) analyses can be reduced to a single partial differential equation. In the same way, movie analysis leads to a single parabolic differential equation. We discuss some applications to image segmentation and movie restoration. The experiments show how accurate and invariant the numerical schemes must be and we compare several (old and new) algorithms by discussing how well they match the axiomatic invariance requirements.


2017 ◽  
Vol 141 (9) ◽  
pp. 1267-1275 ◽  
Author(s):  
Famke Aeffner ◽  
Kristin Wilson ◽  
Nathan T. Martin ◽  
Joshua C. Black ◽  
Cris L. Luengo Hendriks ◽  
...  

Context.— Novel therapeutics often target complex cellular mechanisms. Increasingly, quantitative methods like digital tissue image analysis (tIA) are required to evaluate correspondingly complex biomarkers to elucidate subtle phenotypes that can inform treatment decisions with these targeted therapies. These tIA systems need a gold standard, or reference method, to establish analytical validity. Conventional, subjective histopathologic scores assigned by an experienced pathologist are the gold standard in anatomic pathology and are an attractive reference method. The pathologist's score can establish the ground truth to assess a tIA solution's analytical performance. The paradox of this validation strategy, however, is that tIA is often used to assist pathologists to score complex biomarkers because it is more objective and reproducible than manual evaluation alone by overcoming known biases in a human's visual evaluation of tissue, and because it can generate endpoints that cannot be generated by a human observer. Objective.— To discuss common visual and cognitive traps known in traditional pathology-based scoring paradigms that may impact characterization of tIA-assisted scoring accuracy, sensitivity, and specificity. Data Sources.— This manuscript reviews the current literature from the past decades available for traditional subjective pathology scoring paradigms and known cognitive and visual traps relevant to these scoring paradigms. Conclusions.— Awareness of the gold standard paradox is necessary when using traditional pathologist scores to analytically validate a tIA tool because image analysis is used specifically to overcome known sources of bias in visual assessment of tissue sections.


2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Vesna Ljubojević

Recent studies indicate that placental and umbilical cord morphometry are the factors that may be associated with pregnancy complications, such as fetal growth restriction. Recently, placental and umbilical cord morphometry have been performed using digital image analysis. The aim of this study was to determine the morphometric parameters of placentas using digital image analysis. Material and methods: The digital imaging analysis of twenty placentas and umbilical cord were performed using Image Analysis LAS V4.3 software. Results: The length of the placentas was 191,77 mm ± 35,86 mm (mean ± standard deviation). The width of the placentas was 166,01 mm ± 19,01 mm. The placental surface area was 24495,13 mm2 ± 7038,86 mm2. The insertion of the umbilical cord to the placenta was central in 50 %, peripheral in 37,50 % and marginal in 12,5 % of analyzed placentas. The average distance of the umbilical cord insertion from the nearest placental margin was 38,89 mm ± 28,39 mm. The umbilical cord diameter at the insertion site was 21,16 mm± 5.69 mm. The diameter of the umbilical cord two centimeters from the insertion site was 12,36 mm ± 3,45 mm. Conclusion: Digital image analysis enables obtaining the objective morphometric parameters of the placenta and umbilical cord. The obtained morphometric parameters of the placenta and umbilical cord for our population are comparable to results of previous studies and open further placental research directions for the development of the screening method.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anna Ray Laury ◽  
Sami Blom ◽  
Tuomas Ropponen ◽  
Anni Virtanen ◽  
Olli Mikael Carpén

AbstractHigh-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist review of histologic slides provides no prognostic or predictive information, which is in sharp contrast to almost all other carcinoma types. Deep-learning based image analysis has recently been able to predict outcome and/or identify morphology-based representations of underlying molecular alterations in other tumor types, such as colorectal carcinoma, lung carcinoma, breast carcinoma, and melanoma. Using a carefully stratified HGSC patient cohort consisting of women (n = 30) with similar presentations who experienced very different treatment responses (platinum free intervals of either ≤ 6 months or ≥ 18 months), we used whole slide images (WSI, n = 205) to train a convolutional neural network. The neural network was trained, in three steps, to identify morphologic regions (digital biomarkers) that are highly associating with one or the other treatment response group. We tested the classifier using a separate 22 slide test set, and 18/22 slides were correctly classified. We show that a neural network based approach can discriminate extremes in patient response to primary platinum-based chemotherapy with high sensitivity (73%) and specificity (91%). These proof-of-concept results are novel, because for the first time, prospective prognostic information is identified specifically within HGSC tumor morphology.


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