DocumentCode
3321794
Title
Computed Tomography CAD system for monitoring and modeling the evolution of lung cancer nodule
Author
Uriondo, Iván Ornes ; Arroyo, José Luis García ; Zapirain, Begoña García ; Zorrilla, Amaia Méndez
Author_Institution
Deustotech-Life, Univ. of Deusto, Bilbao, Spain
fYear
2011
fDate
14-17 Dec. 2011
Firstpage
484
Lastpage
489
Abstract
This paper presents research work carried out into lung cancer taking into account that the number of patients with this pathology increases every year. The authors have developed a new CAD software tool and a complete stack of Computed Tomography image processing algorithms, ail integrated in the same platform, suitable for medical radiologists and oncologists to properly control cancer evolution and to calculate quantitative values for its characterization. At the current moment we have a database on 11 patients who have been successfully tested and a total of 69 lung nodules. The growth rates were classified into 3 main types, slow growth 0.3 mm3/day, medium growth 0.7 mm3/day and high growth rate 1.2 mm3/day. From the 69 nodules studied, 14 were labeled with a slow rate, 25 as a medium rate and 27 with a high rate; 3 of them show no growth or even negative growth. In the future, the database is expected to be enlarged with more patients so that numerical data can be obtained, and more algorithms are expected to be developed including new parameters to complete the statistical studies and mathematical modeling.
Keywords
CAD; cancer; computerised monitoring; computerised tomography; diagnostic radiography; image segmentation; lung; medical image processing; radiology; CAD software tooi; computed tomography; image processing algorithms; image segmentation; lung cancer nodule; mathematical modeling; medical radiologists; numerical data; oncologists; pathology; Algorithm design and analysis; Biomedical imaging; Computed tomography; Design automation; Image segmentation; Lungs; Three dimensional displays; 3D Image Segmentation; Computed Tomography; Lung cancer evolution; Nodule growth; Pattern recognition; Template matching;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Information Technology (ISSPIT), 2011 IEEE International Symposium on
Conference_Location
Bilbao
Print_ISBN
978-1-4673-0752-9
Electronic_ISBN
978-1-4673-0751-2
Type
conf
DOI
10.1109/ISSPIT.2011.6151610
Filename
6151610
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