scholarly journals Quantitative Computed Tomography Classification of Lung Nodules

2016 ◽  
Vol 40 (4) ◽  
pp. 589-595 ◽  
Author(s):  
David S. Gierada ◽  
David G. Politte ◽  
Jie Zheng ◽  
Kenneth B. Schechtman ◽  
Bruce R. Whiting ◽  
...  
Author(s):  
Shabana Rasheed Ziyad ◽  
Venkatachalam Radha ◽  
Thavavel Vayyapuri

Background: Lung cancer has become a major cause of cancer-related deaths. Detection of potentially malignant lung nodules is essential for the early diagnosis and clinical management of lung cancer. In clinical practice, the interpretation of Computed Tomography (CT) images is challenging for radiologists due to a large number of cases. There is a high rate of false positives in the manual findings. Computer aided detection system (CAD) and computer aided diagnosis systems (CADx) enhance the radiologists in accurately delineating the lung nodules. Objectives: The objective is to analyze CAD and CADx systems for lung nodule detection. It is necessary to review the various techniques followed in CAD and CADx systems proposed and implemented by various research persons. This study aims at analyzing the recent application of various concepts in computer science to each stage of CAD and CADx. Methods: This review paper is special in its own kind because it analyses the various techniques proposed by different eminent researchers in noise removal, contrast enhancement, thorax removal, lung segmentation, bone suppression, segmentation of trachea, classification of nodule and nonnodule and final classification of benign and malignant nodules. Results: A comparison of the performance of different techniques implemented by various researchers for the classification of nodule and non-nodule has been tabulated in the paper. Conclusion: The findings of this review paper will definitely prove to be useful to the research community working on automation of lung nodule detection.


Rheumatology ◽  
2020 ◽  
Vol 59 (12) ◽  
pp. 3784-3792
Author(s):  
Stephanie Finzel ◽  
Philippe Aegerter ◽  
Georg Schett ◽  
Maria-Antonietta D’Agostino

Abstract Objectives Ultrasound (US) can detect cortical bone lesions in RA. However, not all cortical bone lesions are erosions. Herein, we aimed to define whether US can differentiate between physiological bone channels and pathological erosions in RA and to provide topographic description of their differential localization. Methods RA patients and healthy controls (HC) received US examination of the metacarpophalangeal (MCPJ) and proximal inter-phalangeal (PIPJ) joints adjudicating cortical bone lesions as physiological bone channels or pathological erosions. In a subset of RA patients and HC, high-resolution peripheral quantitative computed tomography (HR-pQCT) of the hand was performed to validate the classification of lesions. Results A total of 40 RA patients and 43 HC were enrolled and totally 771 MCPJ and 638 PIPJ were examined by US, and 94 and 51, respectively, by HR-pQCT. US-defined cortical bone lesions clustered in the lateral part of the MCP (50%) and the dorsal part of the PIPJ (66.7%) in RA. US-defined physiological bone channels clustered in the palmar parts of the MCPJ and PIPJ in both RA (78.8% and 100%, respectively) and HC (51.8% and 80%, respectively). HR-pQCT data confirmed US data with respect to adjudication of physiological bone channels and pathological erosions. Erosions were significantly (all P <0.000001) larger than physiological channels and preferentially localized at radial and ulnar sites, while physiological channels were clustered at palmar sites. Specificity of US was excellent for erosions in RA and for physiological bone channels in HC and RA. Conclusion US allows differentiation between physiological channels and bone erosions in RA.


Haigan ◽  
2001 ◽  
Vol 41 (3) ◽  
pp. 207-211 ◽  
Author(s):  
Keiko Kuriyama ◽  
Miki Nishikubo ◽  
Mitsuko Tsubamoto ◽  
Jun Arisawa ◽  
Chikazumi Kuroda ◽  
...  

2015 ◽  
pp. 2015 ◽  
Author(s):  
Yu-Jen Yu-Jen Chen ◽  
Kai-Lung Hua ◽  
Che-Hao Hsu ◽  
Wen-Huang Cheng ◽  
Shintami Chusnul Hidayati

2013 ◽  
Vol 22 (01) ◽  
pp. 13-17
Author(s):  
J. M. Patsch ◽  
R. Kocijan ◽  
H. Resch ◽  
J. Haschka

ZusammenfassungKnochenstabilität ist durch Knochenvolumen und Mikroarchitektur des Knochens determiniert. Mittels HR-pQCT (high resolution peripheral quantitative computed tomography) steht eine nicht invasive Methode zur Verfügung, um die Mikroarchitektur des Knochens darzustellen. Die Resultate aus zahlreichen Studien geben Rückschlüsse auf unterschiedliche Strukturalterationen im Rahmen von Erkrankungen, die mit einem erhöhten Frakturrisiko einhergehen. Die Knochendichtemessung mittels DXA spiegelt das Frakturrisiko oft nicht adäquat wider. Umso entscheidender ist es, Risikofaktoren in der Wahl der Therapie zu berücksichtigen. Die klinische Relevanz der Resultate aus HR-pQCT-Messungen besteht derzeit dahingehend, dass wertvolle Informationen über Veränderungen der Mikroarchitektur auf Forschungsebene erhoben werden.


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