DESIGNING A NEW CAD SYSTEM FOR PULMONARY NODULE DETECTION IN HIGH RESOLUTION COMPUTED TOMOGRAPHY (HRCT) IMAGES

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

HOSSEINI MOHAMMAD PARSA; SOLTANIAN ZADEH HAMID; AKHLAGHPOOR SHAHRAM; JALALI ALI; BAKHSHAYESH KARAM MEHRDAD

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ) Year:2012 | Volume:70 | Issue:4 Page(s): 250-256

Download Full-Text

Persian Verion

View:

1,589

Download:

Cites:

Information Journal Paper

Title

DESIGNING A NEW CAD SYSTEM FOR PULMONARY NODULE DETECTION IN HIGH RESOLUTION COMPUTED TOMOGRAPHY (HRCT) IMAGES

Author(s)

Keywords

CAD SYSTEMQ2

CT SCANQ2

NODULE DETECTIONQ2

IMAGE PROCESSINGQ2

MEDICAL IMAGE ANALYSISQ2

STATISTICAL PATTERN RECOGNITIONQ2

Abstract

Background: Lung diseases and lung cancer are among the most dangerous diseases with high mortality in both men and women. Lung nodules are abnormal pulmonary masses and are among major lung symptoms. A Computer Aided Diagnosis (CAD) system may play an important role in accurate and early detection of lung nodules. This article presents a new CAD SYSTEM for lung NODULE DETECTION from chest computed tomography (CT) images.Methods: Twenty-five adult patients with lung nodules in their CT SCAN images presented to the National Research Institute of Tuberculosis and Lung Disease, Masih Daneshvari Hospital, Tehran, Iran in 2011-2012 were enrolled in the study. The patients were randomly assigned into two experimental (9 female, 6 male, mean age 43±5.63 yrs) and control (6 female, 4 male, mean age 39±4.91 yrs) groups. A fully-automatic method was developed for detecting lung nodules by employing medical IMAGE PROCESSING and analysis and STATISTICAL PATTERN RECOGNITION algorithms.Results: Using segmentation methods, the lung parenchyma was extracted from 2-D CT images. Then, candidate regions were labeled in pseudo-color images. In the next step, some features of lung nodules were extracted. Finally, an artificial feed forward neural network was used for classification of nodules.Conclusion: Considering the complexity and different shapes of lung nodules and large number of CT images to evaluate, finding lung nodules are difficult and time consuming for physicians and include human error. Experimental results showed the accuracy of the proposed method to be appropriate (P<0.05) for lung NODULE DETECTION.

Cites

No record.

References

No record.

Cite

APA: Copy

HOSSEINI, MOHAMMAD PARSA, SOLTANIAN ZADEH, HAMID, AKHLAGHPOOR, SHAHRAM, JALALI, ALI, & BAKHSHAYESH KARAM, MEHRDAD. (2012). DESIGNING A NEW CAD SYSTEM FOR PULMONARY NODULE DETECTION IN HIGH RESOLUTION COMPUTED TOMOGRAPHY (HRCT) IMAGES. TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ), 70(4), 250-256. SID. https://sid.ir/paper/38199/en

Vancouver: Copy

HOSSEINI MOHAMMAD PARSA, SOLTANIAN ZADEH HAMID, AKHLAGHPOOR SHAHRAM, JALALI ALI, BAKHSHAYESH KARAM MEHRDAD. DESIGNING A NEW CAD SYSTEM FOR PULMONARY NODULE DETECTION IN HIGH RESOLUTION COMPUTED TOMOGRAPHY (HRCT) IMAGES. TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ)[Internet]. 2012;70(4):250-256. Available from: https://sid.ir/paper/38199/en

IEEE: Copy

MOHAMMAD PARSA HOSSEINI, HAMID SOLTANIAN ZADEH, SHAHRAM AKHLAGHPOOR, ALI JALALI, and MEHRDAD BAKHSHAYESH KARAM, “DESIGNING A NEW CAD SYSTEM FOR PULMONARY NODULE DETECTION IN HIGH RESOLUTION COMPUTED TOMOGRAPHY (HRCT) IMAGES,” TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ), vol. 70, no. 4, pp. 250–256, 2012, [Online]. Available: https://sid.ir/paper/38199/en

Related Journal Papers