DocumentCode :
110540
Title :
The LISS—A Public Database of Common Imaging Signs of Lung Diseases for Computer-Aided Detection and Diagnosis Research and Medical Education
Author :
Guanghui Han ; Xiabi Liu ; Feifei Han ; Santika, I. Nyoman Tenaya ; Yanfeng Zhao ; Xinming Zhao ; Chunwu Zhou
Author_Institution :
Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China
Volume :
62
Issue :
2
fYear :
2015
fDate :
Feb. 2015
Firstpage :
648
Lastpage :
656
Abstract :
Lung computed tomography (CT) imaging signs play important roles in the diagnosis of lung diseases. In this paper, we review the significance of CT imaging signs in disease diagnosis and determine the inclusion criterion of CT scans and CT imaging signs of our database. We develop the software of abnormal regions annotation and design the storage scheme of CT images and annotation data. Then, we present a publicly available database of lung CT imaging signs, called LISS for short, which contains 271 CT scans and 677 abnormal regions in them. The 677 abnormal regions are divided into nine categories of common CT imaging signs of lung disease (CISLs). The ground truth of these CISLs regions and the corresponding categories are provided. Furthermore, to make the database publicly available, all private data in CT scans are eliminated or replaced with provisioned values. The main characteristic of our LISS database is that it is developed from a new perspective of CT imaging signs of lung diseases instead of commonly considered lung nodules. Thus, it is promising to apply to computer-aided detection and diagnosis research and medical education.
Keywords :
biomedical education; computerised tomography; diseases; lung; medical diagnostic computing; medical image processing; medical information systems; telemedicine; CISL regions; CT image annotation data; CT image storage scheme; CT imaging sign categories; CT scan inclusion criterion; LISS database characteristics; LISS public database; abnormal region annotation software; common imaging signs; common lung CT imaging signs; computed tomography image annotation data; computed tomography image storage scheme; computed tomography imaging sign categories; computed tomography scan inclusion criterion; computer-aided detection; computer-aided lung disease detection; computer-aided lung disease diagnosis; disease diagnosis research; lung CT imaging sign database; lung computed tomography; medical education; new CT imaging sign perspective; private CT scan data elimination; private CT scan data replacement; provisioned CT scan values; Biomedical imaging; Computed tomography; Databases; Diseases; Lesions; Lungs; CT imaging signs; Computer-aided diagnosis (CAD); computed tomography (CT) imaging signs; lung lesions; medical database; medical education;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2014.2363131
Filename :
6924794
Link To Document :
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