A study of retrieval accuracy of pulmonary nodules based on external attachment

Ashis Kumar Dhara; Sudipta Mukhopadhyay; Shrikant A. Mehre; Niranjan Khandelwal; Nidhi Prabhakar; Mandeep Garg; Naveen Kalra

doi:10.1117/12.2254249

3 March 2017 A study of retrieval accuracy of pulmonary nodules based on external attachment

Ashis Kumar Dhara, Sudipta Mukhopadhyay, Shrikant A. Mehre, Niranjan Khandelwal, Nidhi Prabhakar, Mandeep Garg, Naveen Kalra

Author Affiliations +

Proceedings Volume 10134, Medical Imaging 2017: Computer-Aided Diagnosis; 101343T (2017) https://doi.org/10.1117/12.2254249
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

In this paper, retrieval accuracy of different types of pulmonary nodules is studied. The trainee radiologists could enrich their knowledge using the visual information of the retrieved nodules. In the proposed retrieval system, the pulmonary nodules are segmented using a semi-automated technique. Several 3D features are explored to improve the performance of the proposed retrieval system. A set of relevant shape and texture features is determined for efficient representation of the nodules in the feature space. The proposed CBIR system is validated on a data set of 542 nodules of Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI). The nodules with composite rank of malignancy “1”, “2” are considered as benign and “4”, “5” are considered as malignant. Considering top five retrieved images, the precision of the proposed retrieval system are 84.76%, 80.75%, and 80.34% for well-circumscribed, juxta-pleural, and juxtavascular nodules, respectively.

Citation Download Citation

Ashis Kumar Dhara, Sudipta Mukhopadhyay, Shrikant A. Mehre, Niranjan Khandelwal, Nidhi Prabhakar, Mandeep Garg, and Naveen Kalra "A study of retrieval accuracy of pulmonary nodules based on external attachment", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101343T (3 March 2017); https://doi.org/10.1117/12.2254249

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available