Predicting complexity perception of real world images

The aim of this work is to predict the complexity perception of real world images.We propose a new complexity measure where different image features, based on spatial, frequency and color properties are linearly combined. In order to find the optimal set of weighting coefficients we have applied a Particle Swarm Optimization. The optimal linear combination is the one that best fits the subjective data obtained in an experiment where observers evaluate the complexity of real world scenes on a web-based interface. To test the proposed complexity measure we have performed a second experiment on a different database of real world scenes, where the linear combination previously obtained is correlated with the new subjective data. Our complexity measure outperforms not only each single visual feature but also two visual clutter measures frequently used in the literature to predict image complexity. To analyze the usefulness of our proposal, we have also considered two different sets of stimuli composed of real texture images. Tuning the parameters of our measure for this kind of stimuli, we have obtained a linear combination that still outperforms the single measures. In conclusion our measure, properly tuned, can predict complexity perception of different kind of images

Interfacility Helicopter Ambulance Transport of Neurosurgical Patients: Observations, Utilization, and Outcomes from a Quaternary Level Care Hospital

The clinical benefit of helicopter transport over ground transportation for interfacility transport is unproven. We sought to determine actual practice patterns, utilization, and outcomes of patients undergoing interfacility transport for neurosurgical conditions.We retrospectively examined all interfacility helicopter transfers to a single trauma center during 2008. We restricted our analysis to those transfers leading either to admission to the neurosurgical service or to formal consultation upon arrival. Major exclusion criteria included transport from the scene, death during transport, and transport to any area of the hospital other than the emergency department. The primary outcome was time interval to invasive intervention. Secondary outcomes were estimated ground transportation times from the referring hospital, admitting disposition, and discharge disposition. Of 526 candidate interfacility helicopter transfers to our emergency department in 2008, we identified 167 meeting study criteria. Seventy-five (45%) of these patients underwent neurosurgical intervention. The median time to neurosurgical intervention ranged from 1.0 to 117.8 hours, varying depending on the diagnosis. For 101 (60%) of the patients, estimated driving time from the referring institution was less than one hour. Four patients (2%) expired in the emergency department, and 34 patients (20%) were admitted to a non-ICU setting. Six patients were discharged home within 24 hours. For those admitted, in-hospital mortality was 28%.Many patients undergoing interfacility transfer for neurosurgical evaluation are inappropriately triaged to helicopter transport, as evidenced by actual times to intervention at the accepting institution and estimated ground transportation times from the referring institution. In a time when there is growing interest in health care cost containment, practitioners must exercise discretion in the selection of patients for air ambulance transport--particularly when it may not bear influence on clinical outcome. Neurosurgical evaluation via telemedicine may be one strategy for improving air transport triage