Window classification of brain CT images in biomedical articles.

Xue Z, Antani SK, Long LR, Demner-Fushman D, Thoma GR

AMIA Annu Symp Proc. 2012;2012:1023-9. Epub 2012 Nov 3.

---

Abstract:

Effective capability to search biomedical articles based on visual properties of article images may significantly augment information retrieval in the future. In this paper, we present a new method to classify the window setting types of brain CT images. Windowing is a technique frequently used in the evaluation of CT scans, and is used to enhance contrast for the particular tissue or abnormality type being evaluated. In particular, it provides radiologists with an enhanced view of certain types of cranial abnormalities, such as the skull lesions and bone dysplasia which are usually examined using the " bone window" setting and illustrated in biomedical articles using "bone window images". Due to the inherent large variations of images among articles, it is important that the proposed method is robust. Our algorithm attained 90% accuracy in classifying images as bone window or non-bone window in a 210 image data set.

Xue Z, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Window classification of brain CT images in biomedical articles. 
AMIA Annu Symp Proc. 2012;2012:1023-9. Epub 2012 Nov 3.

PMID | PMCID