Detectability of simulated masses and calcifications in mammography

1998 ◽  
Vol 39 (5) ◽  
pp. 501-506 ◽  
Author(s):  
J. B. Olsen ◽  
A. Skretting
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Breast Tissue ◽  
Detection Threshold ◽  
Roc Curves ◽  
Receiver Operating Characteristics ◽  
Linear Least Squares ◽  
Operating Characteristics ◽  
Least Squares Fit ◽  
Novel Method

Purpose: to develop a method for receiver operating characteristics (ROC) studies in mammography Material and Methods: We developed a phantom based on excised breast tissue and overlay tiles that could be arranged in an arbitrary pattern across the surface of the breast tissue. Some of the tiles contained structures simulating calcifications or masses that produced image contrast near the experimentally determined detection threshold. Based on this phantom, a methodology for performing ROC studies in mammography was developed. the ROC curves were constructed from reporting schemes filled in by radiologists at five different laboratories. the curves were determined by a novel method: a non-linear least-squares fit of a mathematical model to the data Results: There were large differences among the areas under the ROC curves obtained from the five laboratories

Assessment of image quality and total performance in norwegian mammography laboratories

1998 ◽  
Vol 39 (5) ◽  
pp. 507-513
Author(s):  
J. B. Olsen ◽  
A. Skretting ◽  
A. Widmark
Keyword(s):  
Image Quality ◽  
Breast Tissue ◽  
Roc Analysis ◽  
Roc Curves ◽  
Receiver Operating Characteristics ◽  
Mammary Tissue ◽  
Physical Parameters ◽  
Operating Characteristics ◽  
Tissue Phantom ◽  
Total Performance

Purpose: to assess the image quality at different mammography laboratories Material and Methods: Two commercial mammographic test phantoms and one phantom based on excised mammary tissue were used in an assessment of the imaging chain and total performance at 45 Norwegian mammography laboratories. the breast-tissue phantom was used for a receiver operating characteristics (ROC) analysis. This was carried out by putting overlays with identifiable regions (some of which contained a cluster of simulated calcifications) on top of the mammary tissue, and then having a radiologist report the confidence of a finding for each region Results and Conclusion: the areas under the ROC curves were in general high. in nearly all the laboratories, performance was improved when a magnification technique was applied. There were wide variations among the laboratories in total performance as measured by the area under the ROC curve, and also in the physical parameters derived by means of the commercial phantoms. in general, a good ROC performance was associated with a good physical performance in the imaging chain

scholarly journals The Shape of ROC Curves in Shooter Tasks: Implications for Best Practices in Analysis

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Caren M. Rotello ◽  
Laura J. Kelly ◽  
Evan Heit
Keyword(s):  
Best Practices ◽  
Signal Detection ◽  
Roc Curves ◽  
Receiver Operating Characteristics ◽  
Racial Groups ◽  
Operating Characteristics ◽  
Identification Task ◽  
Data Analyses ◽  
Linear Receiver ◽  
First Person Shooter

Four experiments addressed the widely studied issue of the association between racial groups and guns, namely shooter bias, as measured in the first-person shooter task or the weapon identification task, in which participants judge whether a suspect has a weapon or some other item such as a phone (Correll, Park, Judd, & Wittenbrink, 2002; Payne, 2001). Previous studies have employed various analyses that make conflicting, and indeed untested, assumptions about the underlying nature of the data: Analyses of variance and model-based analyses assume linear receiver operating characteristics (ROCs) and signal detection (SDT) analyses assume curved ROCs. The present experiments directly investigated the shape of the ROCs for the weapon identification task, demonstrating that they are curved, and that the majority of previous studies are at risk for inclusion of inappropriate analyses, because they assume linear rather than curved ROCs.

The Application of Digital Filters to the Analysis of Ge and Si(Li) Detector X-Ray Spectra

1979 ◽  
Vol 23 ◽  
pp. 125-131
Author(s):  
L. A. Rayburn
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Digital Filter ◽  
Digital Filters ◽  
Least Squares Method ◽  
Linear Least Squares ◽  
Raw Data ◽  
X Ray ◽  
Peak Structure

AbstractOne of the uncertain aspects in the analysis of x-ray spectra is the determination of the proper background to subtract from the raw data. In those cases where the background is a smoothly varying funct ion of the x-ray energy, the application of a digital filter to the raw data will effectively remove the background leaving only the filtered peak information. These filtered peaks can then be fit by using a non-linear least squares method in conjunction with a suitably chosen mathematical model of the peak structure.

scholarly journals Detecting paraprotein interference on a direct bilirubin assay by reviewing the photometric reaction data

2017 ◽  
Vol 55 (8) ◽  
pp. 1178-1185 ◽  
Author(s):  
Elena García-González ◽  
Maite Aramendía ◽  
Ricardo González-Tarancón ◽  
Naiara Romero-Sánchez ◽  
Luis Rello
Keyword(s):  
Roc Curves ◽  
Direct Bilirubin ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Monoclonal Gammopathies ◽  
Reaction Data ◽  
Receiver Operating

Abstract Background: The direct bilirubin (D-Bil) assay on the AU Beckman Coulter instrumentation can be interfered by paraproteins, which may result in spurious D-Bil results. In a previous work, we took advantage of this fact to detect this interference, thus helping with the identification of patients with unsuspected monoclonal gammopathies. In this work, we investigate the possibility to detect interference based on the review of the photometric reactions, regardless of the D-Bil result. Methods: The D-Bil assay was carried out in a set of 2164 samples. It included a group of 164 samples with paraproteins (67 of which caused interference on the assay), as well as different groups of samples for which high absorbance background readings could also be expected (i.e. hemolyzed, lipemic, or icteric samples). Photometric reaction data were reviewed and receiver operating characteristics (ROC) curves were used to establish a cut-off for absorbance that best discriminates interference. Results: The best cut-off was 0.0100 for the absorbance at the first photometric point of the complementary wavelength in the blank cuvette. Once the optimal cut-off for probable interference was selected, all samples analyzed in our laboratory that provided absorbance values above this cut-off were further investigated to try to discover paraproteins. During a period of 6 months, we detected 44 samples containing paraproteins, five of which belonged to patients with non-diagnosed monoclonal gammopathies. Conclusions: Review of the photometric reaction data permits the systematic detection of paraprotein interference on the D-Bil AU assay, even for samples for which reasonable results are obtained.

Sign in / Sign up

Export Citation Format

Share Document