This new generation of Computer Assisted Detection (CAD) software assists in visualizing, identifying, evaluating, and reporting of pulmonary lesions in digital chest X-rays. With our xLNA Enterprise lung nodule assessment software, suspicious regions are highlighted and marked. You then review or confirm an area that may require further analysis. It’s like another set of eyes on every chest exam.
Increased efficiency
The software can help increase your ability to detect small nodules, and may help increase detection rates of actionable nodules to over 80%, compared with current detection rates of 35 – 65%.1
Easy to use
Employing tools that interact with you in real time means that Philips xLNA is more than a detection aid. It’s also a quantification and diagnostic aid. In fact it’s a real-time interactive diagnostic analysis system that allows you the clinical utility of reporting physician-confirmed lesions, including lung nodules.
Identify nodules more easily: - Choose from chest-specific, contrast-enhanced or nodule-enhanced views
- Quickly mark and select lesions
- Export in DICOM format
Quantify measurements instantly: - Segment and evaluate lesions and nodules in automated or manual mode
- Automatically compute quantitative measurements from segmentation results
- Add additional diagnostic assessment comments
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Assemble clinical reports automatically:
- Start with physician-confirmed diagnostic information (in DICOM format)
- Simply input notes and digital signature
- Automatically secure report with time stamp
- Easily store report in DICOM format; ready for PACS archiving
Improved confidence
You can be confident CAD Chest analysis is based on excellent quality digital images because every DR and CR system benefits from our exclusive UNIQUE image processing technology. xLNA Enterprise assessment can support diagnoses and help you deliver a better quality of patient care.
With thousands of chest X-rays performed every day, the Philips lung nodule assessment solution has the potential to turn every exam into an effective early warning system.
1 Jin Z, Ma D, Song W, Fan L, Wei G, Qian J. Improving radiological interpretation of chest digital radiograph images using a real-time interactive pulmonary nodule analysis system: a cross center study. Updated with the latest experimental results presented at RSNA 2005, Chicago, IL, November, 2005.