Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.
Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community.
Animati Computação Aplicada, Santa Maria-RS, Brasil.
Marcelo
M
Arrais Porto
Universidade Federal de Santa Maria, Universidade Federal de Santa Maria, Santa Maria-RS, Brasil.
Marcos
M
Cordeiro d'Ornellas
D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D006801:Humans; D000069550:Machine Learning; D010363:Pattern Recognition, Automated / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D011873:Radiology Information Systems / Q000145:classification*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*