Modeling of Lung Nodules from LDCT of the Human Chest: Algorithms and Evaluation for CAD Systems

2014 ◽  
pp. 259-290
Author(s):  
Amal A. Farag ◽  
Mostafa Farag ◽  
James Graham ◽  
Salwa Elshazly ◽  
Mohamed al Mogy ◽  
...  
Keyword(s):  
Lung Nodules ◽  
Cad Systems

Computer-Aided Detection of Human Lung Nodules on Computer Tomography Images via Novel Optimized Techniques

2021 ◽  
Vol 17 ◽  
Author(s):  
Lim J. Seelan ◽  
Padma Suresh L. ◽  
Abhilash K.S. ◽  
Vivek P.K.
Keyword(s):  
Lung Cancer ◽  
Lung Nodule ◽  
Curvelet Transform ◽  
Lung Nodules ◽  
Primary Role ◽  
Simple Task ◽  
Cad Systems ◽  
Computer Aided ◽  
Percent Accuracy ◽  
Imaging Algorithms

Background: Globally, the most general reason for huge number of passings is Lung disease. The lung malignancy is the most shocking amongst the tumor types and it plays a significant role for the increase of death rate. It is assessed that nearly 1.2 million persons are determined to have this illness and about 1.1 million individuals are losing their lives due to this sickness in every year. The survival rate is superior if the growth is recognized at earlier periods. The premature identification of lung malignant growth isn't a simple task. Various imaging algorithms are available for detecting the lung cancer. Aim: Computer aided diagnosis scheme is more useful for radiologist in detecting and identifying irregularities in advance and more rapidly. The CAD systems usually focus on identifying and detecting the lung nodules. Staging the lung cancer at its detection need to be focused as the treatment is based on the stage of the cancer. The major drawbacks of existing CAD systems are less accuracy in segmenting the nodule and staging the lung cancer. Objective: The most important intention of this work is to divide the lung nodule from CT image and classify as tumorous cells in order to identify the cancer's position with greater sensitivity, precision, and accuracy than other strategies. Methods: The primary role is defined as follows (i) for de-noising and edge sharpening of lung image, the curvelet transform is used. (ii) The Fuzzy thresholding technique is used to perform lung image binarization and lung boundary corrections. (iii) Segmentation is performed by using K-means algorithm. (iv) By using convolutional neural network (CNN), different stages of lung nodules such as benign and malignant are identified. Results: The proposed classifier achieves a 97.3 percent accuracy. The proposed approach is helpful in detecting lung cancer in its early stages. The proposed classifier achieved a sensitivity of 98.6 percent and a specificity of 96.1 percent. Conclusion: The results demonstrated that the established algorithms can be used to assist a radiologist in classifying lung images into various stages, thus supporting the radiologist in decision making.

scholarly journals Application of CAD systems for the automatic detection of lung nodules

2019 ◽  
Vol 15 ◽  
pp. 100173 ◽  
Author(s):  
Faridoddin Shariaty ◽  
Mojtaba Mousavi
Keyword(s):  
Automatic Detection ◽  
Lung Nodules ◽  
Cad Systems

scholarly journals Lung nodules classification in CT images using texture descriptors

2019 ◽  
Vol 13 (3) ◽  
pp. 38
Author(s):  
Luís Vinícius De Moura ◽  
Caroline Machado Dartora ◽  
Ana Maria Marques da Silva
Keyword(s):  
Logistic Regression ◽  
Texture Feature ◽  
Principal Component ◽  
Texture Features ◽  
Binary Logistic Regression ◽  
Lung Nodules ◽  
Visual Evaluation ◽  
Cad Systems ◽  
Nodule Volume ◽  
Leave One Out

In lung cancer, early diagnosis can improve potentially the prognosis. Accurate interpretation of computed tomography (CT) scans demands significant efforts by radiologists due to the extensive number of slices analyzed in each examination, for each patient. Computer-aided diagnosis (CAD) systems have been applied in several medical fields, but mostly in lung nodules detection and classification. CAD systems for lung lesions classification usually extract different types of features from lesions, such as texture feature, shape and intensity. This exploratory study aims to investigate the performance of lung nodules classification in 2D and 3D CT lesions images using Haralick texture features analysis and binary logistic regression.  Expert radiologists manually segmented from a CT dataset of 17 benign and 20 malignant nodules, which have their anatomopathological results. Haralick features were extracted from 2D lesions images, using the largest cross-section nodule area, and from all nodule volume (3D). Principal Component Analysis (PCA) was applied to reduce texture features dimensionality, showing two and three principal components (PC) can explain 85.8% and 96.25% of data variance for 2D lesions, and 72.4% and 91.7% for 3D lesions, respectively. Binary logistic regression using leave-one-out cross-validation for training and test datasets showed no differences in accuracy (63% - 68%), using two or three PC. The higher sensitivity (75%) was acquired using 2D images with two or three PC, while the higher specificity (65%) was obtained using 3D images with two or three PC. Binary logistic regression using a small number of Haralick texture features showed better accuracy in lung nodules classification than visual evaluation by radiologists, although the limited dataset. Further studies are needed to generalize and improve these results.

Analysing Mechanical Systems in Domestic and Foreign CAD Systems

2018 ◽  
pp. 10-17
Author(s):  
V. A. Martynyuk ◽  
V. A. Trudonoshin ◽  
V. G. Fedoruk
Keyword(s):  
Sheet Material ◽  
The Finite Element Method ◽  
Cad Systems ◽  
Cad System ◽  
Software Products ◽  
Foreign Products ◽  
Nonlinear Algebraic Systems ◽  
Software Product ◽  
Pipeline Design ◽  
The Mathematical Model

The article considers applications of foreign CAD-systems in creating the challenging projects at domestic enterprises and design bureaus. As stated in the article "... presently, there is no domestic CAD-system that could completely replace such foreign products as NX, CATIA, Credo". Besides, due to international cooperation in creating the challenging projects (for example, the project to create a modern wide-body aircraft, proposed jointly with China), it makes sense to use the worldwide known and popular CAD systems (the aforementioned NX, CATIA, Credo). Therefore, in the foreseeable future, we will still have to use foreign software products. Of course, there always remains a question of the reliability of the results obtained. Actually, this question is always open regardless of what software product is used - domestic or foreign. This question has been haunting both developers and users of CAD systems for the last 30 to 40 years. But with using domestic systems, it is much easier to identify the cause of inaccurate results and correct the mathematical models used, the methods of numerical integration applied, and the solution of systems of nonlinear algebraic systems. Everything is much more complicated if we use a foreign software product. All advertising conversations that there is a tool to make the detected errors available to the developers, remain only conversations in the real world. It is easily understandable to domestic users, and, especially, to domestic developers of similar software products. The existing development rates and competition for potential buyers dictate a rigid framework of deadlines for releasing all new versions of the product and introducing the latest developments into commercial product, etc. As a result, the known errors migrate from version to version, and many users have accepted it long ago. Especially, this concerns the less popular tools rather than the most popular applications (modules) of a CAD system. For example, in CAD systems, the "Modeling" module where geometric models of designed parts and assembly units are created has been repeatedly crosschecked. But most of the errors are hidden in applications related to the design of parts from sheet material and to the pipeline design, as well as in applications related to the analysis of moving mechanisms and to the strength or gas dynamic analysis by the finite element method.The article gives a concrete example of a moving mechanism in the analysis of which an error was detected using the mathematical model of external influence (a source of speed) in the NX 10.0 system of Siemens.

THE NEW ALGORITHM OF SOLVING HARMONIC BALANCE EQUATIONS

2019 ◽  
Author(s):  
Vladimir Lantsov ◽  
A. Papulina
Keyword(s):  
Harmonic Balance ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Balance Equations ◽  
Model Order ◽  
Cad Systems ◽  
Computational Costs ◽  
Reduction Methods ◽  
Model Equations

The new algorithm of solving harmonic balance equations which used in electronic CAD systems is presented. The new algorithm is based on implementation to harmonic balance equations the ideas of model order reduction methods. This algorithm allows significantly reduce the size of memory for storing of model equations and reduce of computational costs.

Multi-level 3D Densenets for False-positive Reduction in Lung Nodule Detection Based on Chest Computed Tomography

2020 ◽  
Vol 16 (8) ◽  
pp. 1004-1021
Author(s):  
Xiaoqi Lu ◽  
Yu Gu ◽  
Lidong Yang ◽  
Baohua Zhang ◽  
Ying Zhao ◽  
...  
Keyword(s):  
False Positive ◽  
Contextual Information ◽  
Lung Nodule ◽  
Positive Sample ◽  
Lung Nodules ◽  
Lung Nodule Detection ◽  
Nodule Detection ◽  
Level Information ◽  
Multi Level ◽  
Cade System

Objective: False-positive nodule reduction is a crucial part of a computer-aided detection (CADe) system, which assists radiologists in accurate lung nodule detection. In this research, a novel scheme using multi-level 3D DenseNet framework is proposed to implement false-positive nodule reduction task. Methods: Multi-level 3D DenseNet models were extended to differentiate lung nodules from falsepositive nodules. First, different models were fed with 3D cubes with different sizes for encoding multi-level contextual information to meet the challenges of the large variations of lung nodules. In addition, image rotation and flipping were utilized to upsample positive samples which consisted of a positive sample set. Furthermore, the 3D DenseNets were designed to keep low-level information of nodules, as densely connected structures in DenseNet can reuse features of lung nodules and then boost feature propagation. Finally, the optimal weighted linear combination of all model scores obtained the best classification result in this research. Results: The proposed method was evaluated with LUNA16 dataset which contained 888 thin-slice CT scans. The performance was validated via 10-fold cross-validation. Both the Free-response Receiver Operating Characteristic (FROC) curve and the Competition Performance Metric (CPM) score show that the proposed scheme can achieve a satisfactory detection performance in the falsepositive reduction track of the LUNA16 challenge. Conclusion: The result shows that the proposed scheme can be significant for false-positive nodule reduction task.

ТИРИСТОРНЫЙ ЭФФЕКТ В СВЧ ИС, ИЗГОТОВЛЕННЫХ ПО SIGE БИКМОП-ТЕХНОЛОГИЯМ

2020 ◽  
Vol 96 (3s) ◽  
pp. 612-614
Author(s):  
В.В. Елесина ◽  
И.О. Метелкин
Keyword(s):  
Integrated Circuits ◽  
Extraction Procedure ◽  
Compact Model ◽  
Model Parameters ◽  
Cad Systems ◽  
Parameters Extraction ◽  
Sige Bicmos ◽  
Bicmos Integrated Circuits ◽  
Basic Parameters ◽  
Radiation Induced

Проведен анализ случаев возникновения тиристорного эффекта в СВЧ ИС, изготовленных по технологии SiGe БиКМОП, при воздействии ионизирующего излучения. Рассмотрены области СВЧ ИС, чувствительные к возникновению ТЭ, определены основные параметры тиристорных структур. Проведена апробация подхода к восстановлению параметров схемно-топологической радиационно-ориентированной модели тиристорной структуры для САПР. The paper analyzes ionizing radiation induced latchup in microwave SiGe BiCMOS integrated circuits (ICs). Critical parts of ICs sensitive to latchup have been identified and basic parameters of corresponding parasitic thyristor structures have been determined. An approach has been approved to the thyristor structure compact model parameters extraction procedure intended for use in CAD systems.

scholarly journals Shape-Based Computer-Aided Detection of Lung Nodules in Thoracic CT Images

2009 ◽  
Vol 56 (7) ◽  
pp. 1810-1820 ◽  
Author(s):  
Xujiong Ye ◽  
Xinyu Lin ◽  
J. Dehmeshki ◽  
G. Slabaugh ◽  
G. Beddoe
Keyword(s):  
Ct Images ◽  
Lung Nodules ◽  
Computer Aided Detection ◽  
Thoracic Ct ◽  
Computer Aided

scholarly journals Sensitivity of Thoracic Digital Tomosynthesis (DTS) for the Identification of Lung Nodules

2015 ◽  
Vol 29 (1) ◽  
pp. 141-147 ◽  
Author(s):  
Steve G. Langer ◽  
Brian D. Graner ◽  
Beth A. Schueler ◽  
Kenneth A. Fetterly ◽  
James M. Kofler ◽  
...  
Keyword(s):  
Lung Nodules ◽  
Digital Tomosynthesis
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