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OBJECTIVETo determine the clinical diagnoses associated with the National Healthcare Safety Network (NHSN) pneumonia (PNEU) or lower respiratory infection (LRI) surveillance eventsDESIGNRetrospective chart reviewSETTINGA convenience sample of 8 acute-care hospitals in PennsylvaniaPATIENTSAll patients hospitalized during 2011–2012METHODSMedical records were reviewed from a random sample of patients reported to the NHSN to have PNEU or LRI, excluding adults with ventilator-associated PNEU. Documented clinical diagnoses corresponding temporally to the PNEU and LRI events were recorded.RESULTSWe reviewed 250 (30%) of 838 eligible PNEU and LRI events reported to the NHSN; 29 reported events (12%) fulfilled neither PNEU nor LRI case criteria. Differences interpreting radiology reports accounted for most misclassifications. Of 81 PNEU events in adults not on mechanical ventilation, 84% had clinician-diagnosed pneumonia; of these, 25% were attributed to aspiration. Of 43 adult LRI, 88% were in mechanically ventilated patients and 35% had no corresponding clinical diagnosis (infectious or noninfectious) documented at the time of LRI. Of 36 pediatric PNEU events, 72% were ventilator associated, and 70% corresponded to a clinical pneumonia diagnosis. Of 61 pediatric LRI patients, 84% were mechanically ventilated and 21% had no corresponding clinical diagnosis documented.CONCLUSIONSIn adults not on mechanical ventilation and in children, most NHSN-defined PNEU events corresponded with compatible clinical conditions documented in the medical record. In contrast, NHSN LRI events often did not. As a result, substantial modifications to the LRI definitions were implemented in 2015.Infect Control Hosp Epidemiol 2016;37:818–824

Computer vision techniques have been applied for rapid and accurate structure recovery in many fields. Most methods perform poorly in areas containing little or no texture and in the presence of repetitive patterns. We present a portable, cost-effective pattern projector system powered by the flash of a camera, to aid the reconstruction of such areas. No calibration is required between the camera-projector, projector-scene, or pattern. We demonstrate the effectiveness of our system on various representative surfaces like stone, metal, clay, porcelain, and natural fibers, with different inherent colors/textures. A pipeline is presented to automatically generate textured, true-scale metric models, that can be used for quantitative studies or visualization. The practicability of our system is explored in the specific area of digital archiving of historically significant objects. We show results from field trips to 12th century temples at Belur and Halebidu in South India and objects from the Wintherthur museum, Delaware, USA.

Computer vision techniques have been applied for rapid and accurate structure recovery in many fields. Most methods perform poorly in areas containing little or no texture and in presence of repetitive patterns. We present a portable, cost-effective pattern projector system powered by the flash of a camera, to aid the reconstruction of such areas. No calibration is required between the camera-projector, projector-scene or pattern. We demonstrate the effectiveness of our system on various representative surfaces like metal, clay, porcelain and natural fibres with different inherent colors/textures. A pipeline is presented to automatically generate textured, true scale metric models, which can be used for quantitative studies or visualization. The practability of our system is explored in the specific area of digital archiving of historically significant objects.