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Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database
- Source :
- European Radiology, 26, 2139-2147, European Radiology, 26, 7, pp. 2139-2147, European Radiology
- Publication Year :
- 2016
-
Abstract
- Objectives To benchmark the performance of state-of-the-art computer-aided detection (CAD) of pulmonary nodules using the largest publicly available annotated CT database (LIDC/IDRI), and to show that CAD finds lesions not identified by the LIDC's four-fold double reading process. Methods The LIDC/IDRI database contains 888 thoracic CT scans with a section thickness of 2.5 mm or lower. We report performance of two commercial and one academic CAD system. The influence of presence of contrast, section thickness, and reconstruction kernel on CAD performance was assessed. Four radiologists independently analyzed the false positive CAD marks of the best CAD system. Results The updated commercial CAD system showed the best performance with a sensitivity of 82 % at an average of 3.1 false positive detections per scan. Forty-five false positive CAD marks were scored as nodules by all four radiologists in our study. Conclusions On the largest publicly available reference database for lung nodule detection in chest CT, the updated commercial CAD system locates the vast majority of pulmonary nodules at a low false positive rate. Potential for CAD is substantiated by the fact that it identifies pulmonary nodules that were not marked during the extensive four-fold LIDC annotation process. Key Points BL CAD systems should be validated on public, heterogeneous databases. BL The LIDC/IDRI database is an excellent database for benchmarking nodule CAD. BL CAD can identify the majority of pulmonary nodules at a low false positive rate. BL CAD can identify nodules missed by an extensive two-stage annotation process.
- Subjects :
- medicine.medical_specialty
Lung Neoplasms
Databases, Factual
Computer-assisted diagnosis
Solitary pulmonary nodule
Vascular damage Radboud Institute for Health Sciences [Radboudumc 16]
computer.software_genre
Sensitivity and Specificity
Computer Applications
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
medicine
Humans
Radiology, Nuclear Medicine and imaging
Computer-assisted
Diagnosis, Computer-Assisted
cardiovascular diseases
Lung
Retrospective Studies
Multiple Pulmonary Nodules
Database
business.industry
Reproducibility of Results
Double reading
General Medicine
Image interpretation, computer-assisted
Computer aided detection
3. Good health
Tomography x ray computed
Image interpretation
Radiology Nuclear Medicine and imaging
030220 oncology & carcinogenesis
Radiographic Image Interpretation, Computer-Assisted
Radiology
Lung cancer
Tomography, X-Ray Computed
business
computer
Rare cancers Radboud Institute for Health Sciences [Radboudumc 9]
Subjects
Details
- ISSN :
- 09387994
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- European Radiology
- Accession number :
- edsair.doi.dedup.....75286fb943dd64eac8b1b479bddcc134