A Multistage Approach to Improve Performance of Computer-Aided Detection of Pulmonary Embolisms Depicted on CT Images


Authors : Shraddha kokane, Swapnaja Kumbhar, Shweta Kutte, A. G. Patil.

Volume/Issue : Volume 2 - 2017, Issue 4 - April

Google Scholar : https://goo.gl/1WlIhR

Scribd : https://goo.gl/61n4I8

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction;4) false-positive (FP) reduction using an artificial neural network(ANN); and 5) a multifeature-based k nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance:1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete “redundant” features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination.

Keywords : Computer-aided detection (CAD), false positive (FP) reduction, feature selection , pulmonary embolism, tobogganing. genetic algorithm (GA).

CALL FOR PAPERS


Paper Submission Last Date
31 - December - 2020

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe