Papers Published

1. Castella, C; Eckstein, MP; Abbey, CK; Kinkel, K; Verdun, FR; Saunders, RS; Samei, E; Bochud, FO, Mass detection on mammograms: influence of signal shape uncertainty on human and model observers., J Opt Soc Am A Opt Image Sci Vis, vol. 26 no. 2 (February, 2009), pp. 425-436 [19183697], [doi] .
   (last updated on 2025/04/05)

   Abstract:
   We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

   Keywords:
   Artificial Intelligence* • Breast Neoplasms • Computer Simulation • Early Detection of Cancer* • Humans • Mammography • Observer Variation • Radiographic Image Interpretation, Computer-Assisted • Uncertainty* • methods* • radiography