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
Link To Document :
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