scholarly journals Complex Nodule Shape

2020 ◽  
Author(s):  
Keyword(s):  
Nodule Shape

A Novel Approach for Computer-Aided Diagnosis for Distinction Between Benign and Malignant of Lung Nodules Based on Machine Learning Techniques

2018 ◽  
pp. 281-290
Author(s):  
Shashidhara Bola
Keyword(s):  
False Positive Rate ◽  
Lung Nodule ◽  
Machine Learning Techniques ◽  
Lung Nodules ◽  
Data Set ◽  
Novel Approach ◽  
Learning Techniques ◽  
Nodule Shape ◽  
Positive Rate ◽  
Aided Diagnosis

A new method is proposed to classify the lung nodules as benign and malignant. The method is based on analysis of lung nodule shape, contour, and texture for better classification. The data set consists of 39 lung nodules of 39 patients which contain 19 benign and 20 malignant nodules. Lung regions are segmented based on morphological operators and lung nodules are detected based on shape and area features. The proposed algorithm was tested on LIDC (lung image database consortium) datasets and the results were found to be satisfactory. The performance of the method for distinction between benign and malignant was evaluated by the use of receiver operating characteristic (ROC) analysis. The method achieved area under the ROC curve was 0.903 which reduces the false positive rate.

Root system variability in common legumes in Central Europe

Biologia ◽  
2012 ◽  
Vol 67 (1) ◽  
Author(s):  
Lucie Chmelíková ◽  
Michal Hejcman
Keyword(s):  
Root System ◽  
Root Systems ◽  
Life Forms ◽  
Root Diameter ◽  
Legume Species ◽  
Minimum Diameter ◽  
Lupinus Polyphyllus ◽  
Nodule Shape ◽  
System Variability ◽  
Trifolium Arvense

AbstractThe aim of this study was to provide an overview of field measured root systems of common legume species growing under different environmental conditions in the Czech Republic. The plants, 214 individuals of 21 selected legume species from the tribes Galegeae (Astragalus glycyphyllos, Lupinus polyphyllus), Genisteae (Cytisus scoparius, Genista tinctoria), Loteae (Anthyllis vulneraria, Lotus corniculatus, Securigera varia), Trifolieae (Trifolium arvense, T. campestre, T. medium, T. pratense, T. repens) and Vicieae (Lathyrus pratensis, L. sylvestris, Vicia angustifolia, V. cracca, V. hirsuta), were collected using the monolith method from 27 sites.A rhizome was present in seven species and the maximum branching order was three for 15 species and five for five species. Recovery buds were recorded on the root system of eight species and woodiness was recorded in 11 species. Root diameter ranged from 1 to 12 mm — the minimum diameter was recorded in annuals and the maximum in perennials. The colour of the root system ranged from light to dark. In six species, young roots were light and older roots were dark. Globose, cylindrical, branched, fan-like and ruff-like nodules were recorded. Only one type of nodule shape was recorded in 11 species, two in seven species and three or four in three species. Nodules measured up to 2 mm in nine species, from 2 to 4 mm in three species and more than 4 mm in nine species. Legume root systems are highly variable and the variability was due to Raunkier’s life forms rather than membership of a tribe.

Multi-Scaling Homogenization Process for Nodular Cast Iron Using BEM

2017 ◽  
Vol 08 (03n04) ◽  
pp. 1740005
Author(s):  
Adrián Alberto Betancur Arroyave ◽  
Carla Tatiana Mota Anflor
Keyword(s):  
Cast Iron ◽  
Effective Properties ◽  
Heterogeneous Materials ◽  
Nodular Cast Iron ◽  
External Boundary ◽  
Element Formulation ◽  
Modeling Tools ◽  
Homogenization Process ◽  
Nodule Shape ◽  
Good Agreement

In this work, a multi-scaling homogenization process using boundary element formulation (BEM) for modeling a two-dimensional multi-phase microstructure containing irregular’s inclusions is presented. The BEM is very attractive for multiscale modeling tools for heterogeneous materials. In this approach, the iterative inhomogeneity discretization of the external boundary is disregarded, leading to a computational low cost. This approach was used for solving the elastic problem of a representative volume element (RVE) and the field theory medium. The main goal relies on finding the effective properties of micro-heterogeneous materials within a homogeneous and orthotropic matrix. Expressions for evaluating the effective properties under Plane Stress (PT) for orthotropic materials were also presented. Generally, the numerical models consider the graphite nodules as voids for GGG-40 and the roundness is close circular geometry. In this sense, a nodular cast iron GGG-40 microgram was obtained by X-ray computed tomography and Laser Confocal Microscope System, allowing the modeling of the true nodule shape. The numerical results showed good agreement with the experimental tests. The inclusions of graphite were considered as voids in the material matrix. Experimental stress–strain tests and micrographic analysis were used to determine the Young’s modulus, spatial distributions, as well as, nodule shape. The numerical in this work was compared with the obtained experimental results in this work. The comparison between the obtained experimental data with those available in the literature also showed good agreement.

scholarly journals Shape analysis for classification of breast nodules on digital ultrasound images

2019 ◽  
Vol 13 (2) ◽  
pp. 837
Author(s):  
Hanung Adi Nugroho ◽  
Hesti Khuzaimah Nurul Yusufiyah ◽  
Teguh Bharata Adji ◽  
Widhia K.Z Oktoeberza
Keyword(s):  
Shape Analysis ◽  
Median Filter ◽  
Extraction Process ◽  
Input Image ◽  
Speckle Reduction ◽  
Ultrasound Images ◽  
Invariant Moments ◽  
Nodule Shape ◽  
Breast Nodule

<span>One of the imaging modalities for early detection of breast cancer malignancy is ultrasonography (USG).  The malignancy can be analysed from the characteristic of nodule shape.  This study aims to develop a method for classifying the shape of breast nodule into two classes, namely regular and irregular classes.  The input image is pre-processed by using the combination of adaptive median filter and speckle reduction bilateral filtering (SRBF) to reduce speckle noises and to eliminate the image label.  Afterwards, the filtered image is segmented based on active contour followed by feature extraction process.  Nine extracted features, i.e. roundness, slimness and seven features of invariant moments, are used to classify nodule shape using multi-layer perceptron (MLP).  The performance of the proposed method is evaluated using 105 breast nodule images which comprise of 57 regular and 48 irregular nodule images.  The results of classification process achieve the level of accuracy, sensitivity and specificity at 96.20%, 97.90% and 94.70%, respectively.  These results indicate that the proposed method successfully classifies the breast nodule images based on shape analysis.</span>

Thyroid Nodule Shape and Prediction of Malignancy

Thyroid ◽  
2004 ◽  
Vol 14 (11) ◽  
pp. 953-958 ◽  
Author(s):  
Erik K. Alexander ◽  
Ellen Marqusee ◽  
Joseph Orcutt ◽  
Carol B. Benson ◽  
Mary C. Frates ◽  
...  
Keyword(s):  
Thyroid Nodule ◽  
Nodule Shape

Characterizing pulmonary nodule shape using a boundary-region approach

2009 ◽  
Author(s):  
William H. Horsthemke ◽  
Daniela S. Raicu ◽  
Jacob D. Furst
Keyword(s):  
Pulmonary Nodule ◽  
Boundary Region ◽  
Nodule Shape ◽  
Region Approach

The Use of Spheroidal Graphite Cast Irons to Develop Forgeability Criteria Based on Local Strain Measurements

1989 ◽  
Vol 111 (1) ◽  
pp. 26-31 ◽  
Author(s):  
J. Shi ◽  
M. Ghoreshy ◽  
R. W. Smith ◽  
J. J. M. Too
Keyword(s):  
Shape Change ◽  
Local Strain ◽  
Major Axis ◽  
Minor Axis ◽  
Spheroidal Graphite ◽  
Cast Irons ◽  
Strain Measurements ◽  
Area Of Interest ◽  
The Matrix ◽  
Nodule Shape

An attempt has been made to develop forgeability criteria based on data obtained from local strain measurements. Nodular case iron has been used as the modelling material because its microstructure may be manipulated to contain near-spherical graphite nodules which are suitable for the study of deformation, foregeability, etc. Cracking will occur under certain deformation conditions which may be determined by following the changes in spherulite/nodule shape and habit. Local strain in any area of interest may be determined by measuring the shape change of the previously spherical nodules in terms of an aspect ratio b/a (a = major axis, b = minor axis of the deformed nodules) from specimens sectioned after deformation. A wide variety of forgeabilities can be obtained by changing the microstructure and composition of the matrix.

scholarly journals Nodule Shape

2020 ◽  
Author(s):  
Keyword(s):  
Nodule Shape

scholarly journals Efektivitas Penggunaan Seleksi Ciri CFS pada Klasifikasi Ciri Bentuk Nodul Kanker Payudara dengan Citra Ultrasonografi

2021 ◽  
Vol 3 (1) ◽  
pp. 11-18
Author(s):  
Hesti Khuzaimah Nurul Yusufiyah ◽  
Juan Pandu Gya Nur Rochman
Keyword(s):  
Breast Cancer ◽  
Feature Selection ◽  
Sensitivity And Specificity ◽  
Selection Process ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Shape Features ◽  
Characteristic Shape ◽  
Nodule Shape ◽  
Shape Characteristics

The implementation of nodule shape characteristics is one of the parameters used in determining breast cancer malignancy. Mathematical calculations are used as a second decision to strengthen radiologists in determining breast cancer malignancy using ultrasound images (USG). The method used in this research is to filter ultrasound images that contain speckle noise, then continue the segmentation process, extracting shape features, selecting shape features, and classifying them. The feature selection process using Correlated based Feature Selection (CFS) is used to select the dominant shape features in the image. The classification results obtained show that the results of feature selection using CFS can improve the results of image accuracy, sensitivity and specificity, so as to be able to better distinguish the characteristic shape of the cancer nodule.

Automated Estimation of In-plane Nodule Shape in Chest Tomosynthesis Images

2015 ◽  
pp. 20-23 ◽  
Author(s):  
J. Arvidsson ◽  
A. Chodorowski ◽  
C. Söderman ◽  
A. Svalkvist ◽  
Å. A. Johnsson ◽  
...  
Keyword(s):  
Nodule Shape
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