Segmentation of cancellous bone from high-resolution computed tomography images: influence on trabecular bone measurements

2002 ◽  
Vol 21 (4) ◽  
pp. 354-362 ◽  
Author(s):  
A. Elmoutaouakkil ◽  
F. Peyrin ◽  
J. Elkafi ◽  
A.-M. Laval-Jeantet
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Trabecular Bone ◽  
Cancellous Bone ◽  
High Resolution Computed Tomography ◽  
Computed Tomography Images

scholarly journals Identification of emphysema patterns in high resolution computed tomography images

2017 ◽  
Vol 4 (1) ◽  
pp. 16
Author(s):  
Musibau A. Ibrahim ◽  
Oladotun A. Ojo ◽  
Peter A. Oluwafisoye
Keyword(s):  
Computed Tomography ◽  
Fractal Dimension ◽  
High Resolution ◽  
Hölder Exponent ◽  
High Resolution Computed Tomography ◽  
Box Counting ◽  
Computed Tomography Images ◽  
Local Intensity ◽  
Box Counting Method

Fractal dimension (FD) is a very useful metric for the analysis of image structures with statistically self-similar properties. It has applications in areas such as texture segmentation, shape classification and analysis of medical images. Several approaches can be used for calculating the fractal dimension of digital images; the most popular method is the box-counting method. It is also very challenging and difficult to classify patterns in high resolution computed tomography images (HRCT) using this important descriptor. This paper applied the Holder exponent computation of the local intensity values for detecting the emphysema patterns in HRCT images. The absolute differences between the normal and the abnormal regions in the images are the key for a successful classification of emphysema patterns using the statistical analysis. The results obtained in this paper demonstrated the effectiveness of the predictive power of the features extracted from the Holder exponent in the analysis and classification of HRCT images. The overall classification accuracy achieved in lung tissue layers is greater than 90%, which is an evidence to prove the effectiveness of the methods investigated in this paper.

scholarly journals Paracoccidioidomycosis: level of pulmonary sequelae in high resolution computed tomography images from patients of two endemic regions of Brazil

2017 ◽  
Vol 7 (3) ◽  
pp. 318-325 ◽  
Author(s):  
Diana Rodrigues de Pina ◽  
Matheus Alvarez ◽  
Guilherme Giacomini ◽  
Ana Luiza Menegatti Pavan ◽  
Carlos Ivan Andrade Guedes ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
High Resolution Computed Tomography ◽  
Computed Tomography Images

scholarly journals Classification of High-Resolution Computed Tomography Manifestations for COVID-19 Patients: A Systematic Review

2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Sanaz Alibabaei ◽  
Elham Rohollahpour ◽  
Marziyeh Tahmasbi
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
False Negative ◽  
Disease Process ◽  
Common Finding ◽  
High Resolution Computed Tomography ◽  
Computed Tomography Images ◽  
Peripheral Areas ◽  
Severity Of The Disease ◽  
Low Sensitivity

Context: The early detection of COVID-19 is of paramount importance for the disease treatment and control. As real-time reverse-transcription polymerase chain reaction indicates a low sensitivity, the computed tomography of patients' chest can play an effective role in the diagnosis of COVID-19, particularly for patients with false-negative RT-PCR tests. It is also effective in monitoring the clinical trends and assessing the severity of the disease. Objectives: Accordingly, this study aimed to review the different manifestations of the COVID-19 infections in High-Resolution Computed Tomography images of patients' chests and analyze the distribution of the disease in the lungs. The results can contribute to providing a comprehensive and concise reference on the appearance of various types of involvement and lung lesions and the extent of these lesions in the COVID-19 patients. Data Sources: We systematically searched four major indexing databases (namely PubMed, Science Direct, Google Scholar, and Cochrane Central) for articles published by May 2021 using the following keywords: High-Resolution Computed Tomography (HRCT), COVID-19, and Manifestations. Results: Overall, 29 studies addressing the role of HRCT in detecting and evaluating the manifestations of the COVID-19 infection in patients' lungs as Ground Glass Opacification (GGO), Consolidation, Irregular Solid Nodules, Fibrous Stripes, Crazy Paving Pattern, Air Bronchogram Sign, etc. were reviewed. Conclusions: GGO was the most common finding, as reported in 96.6% of the reviewed articles, followed by Consolidations (65.5%) and Irregular Solid Nodules (55.2%). Most patients revealed the disease process as a bilateral distribution in the peripheral areas of the lung.

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