FMRI Clustering and False Positive Rates

Recently, Eklund et al. (2016) analyzed clustering methods in standard FMRI packages: AFNI (which we maintain), FSL, and SPM [1]. They claimed: 1) false positive rates (FPRs) in traditional approaches are greatly inflated, questioning the validity of "countless published fMRI studies"; 2) nonparametric methods produce valid, but slightly conservative, FPRs; 3) a common flawed assumption is that the spatial autocorrelation function (ACF) of FMRI noise is Gaussian-shaped; and 4) a 15-year-old bug in AFNI's 3dClustSim significantly contributed to producing "particularly high" FPRs compared to other software. We repeated simulations from [1] (Beijing-Zang data [2], see [3]), and comment on each point briefly.Comment: 3 pages, 1 figure. A Letter accepted in PNA

Retrospective analysis of suspicious non palpable breast lesions from : the initial years of the Breast Unit in Malta

Aim: The aim of this retrospective study was to analyse the false positive rate of suspicious non palpable breast lesions detected by ultrasonography and mommography. Method: the data was collected from the first seven years (2000-2007) since the set up of the Breast Unit in Malta. Results: The results showed that the false positive rate for suspicious breast lesions detected by ultrasound and mammography were 84% and 57.6% respectively. The overall false positive rate was 62.5%. Conclusion: The overall false positive rate for suspicious breast lesions detected by both radiographic modalities is high in our unit when compared to that of other countries. Suggestions for improvement are discussed.peer-reviewe

A novel technique for reducing false positive detections in CAD-CTC

Computed tomography colonoscopy (CTC) is an emerging alternative to conventional colonoscopy for colorectal cancer screening. A series of computer assisted diagnosis (CAD) techniques have been developed for use in CTC. Although high levels of accuracy for polyp detection have been reported, the problem of excessive false positive detections still warrants attention. We present a CAD-CTC technique that has been developed specifically to reduce the number of false positive detections without compromising polyp detection accuracy. The technique incorporates a novel intermediate stage that restructures initial polyp candidates so that they conform more closely to the shape of actual polyps. The restructuring process causes false positives to expand to include more false positive characteristics, whereas, actual polyps retain their original polyp-like characteristics. An evaluation of the documented technique demonstrated that it can be successfully applied to the majority of polyp candidates, and that its use can reduce the number of false positive detections by up to 57.8%

A study on the false positive rate of Stegdetect

In this paper we analyse Stegdetect, one of the well-known image steganalysis tools, to study its false positive rate. In doing so, we process more than 40,000 images randomly downloaded from the Internet using Google images, together with 25,000 images from the ASIRRA (Animal Species Image Recognition for Restricting Access) public corpus. The aim of this study is to help digital forensic analysts, aiming to study a large number of image files during an investigation, to better understand the capabilities and the limitations of steganalysis tools like Stegdetect. The results obtained show that the rate of false positives generated by Stegdetect depends highly on the chosen sensitivity value, and it is generally quite high. This should support the forensic expert to have better interpretation in their results, and taking the false positive rates into consideration. Additionally, we have provided a detailed statistical analysis for the obtained results to study the difference in detection between selected groups, close groups and different groups of images. This method can be applied to any steganalysis tool, which gives the analyst a better understanding of the detection results, especially when he has no prior information about the false positive rate of the tool

APHRODITE: an Anomaly-based Architecture for False Positive Reduction

We present APHRODITE, an architecture designed to reduce false positives in network intrusion detection systems. APHRODITE works by detecting anomalies in the output traffic, and by correlating them with the alerts raised by the NIDS working on the input traffic. Benchmarks show a substantial reduction of false positives and that APHRODITE is effective also after a "quick setup", i.e. in the realistic case in which it has not been "trained" and set up optimall

Pre-Spectroscopic False Positive Elimination of Kepler Planet Candidates

Ten days of commissioning data (Quarter 0) and thirty-three days of science data (Quarter 1) yield instrumental flux timeseries of ~150,000 stars that were combed for transit events, termed Threshold Crossing Events (TCE), each having a total detection statistic above 7.1-sigma. TCE light curves are modeled as star+planet systems. Those returning a companion radius smaller than 2R_J are assigned a KOI (Kepler Object of Interest) number. The raw flux, pixel flux, and flux-weighted centroids of every KOI are scrutinized to assess the likelihood of being an astrophysical false-positive versus the likelihood of a being a planetary companion. This vetting using Kepler data is referred to as data validation. Herein, we describe the data validation metrics and graphics used to identify viable planet candidates amongst the KOIs. Light curve modeling tests for a) the difference in depth of the odd- versus even-numbered transits, b) evidence of ellipsoidal variations, and c) evidence of a secondary eclipse event at phase=0.5. Flux-weighted centroids are used to test for signals correlated with transit events with a magnitude and direction indicative of a background eclipsing binary. Centroid timeseries are complimented by analysis of images taken in-transit versus out-of-transit, the difference often revealing the pixel contributing the most to the flux change during transit. Examples are shown to illustrate each test. Candidates passing data validation are submitted to ground-based observers for further false-positive elimination or confirmation/characterization.Comment: submitted to Astrophysical Journal Letter

Constraining the False Positive Rate for Kepler Planet Candidates with Multi-Color Photometry from the GTC

Using the OSIRIS instrument installed on the 10.4-m Gran Telescopio Canarias (GTC) we acquired multi-color transit photometry of four small (Rp < 5 R_Earth) short-period (P < 6 days) planet candidates recently identified by the Kepler space mission. These observations are part of a program to constrain the false positive rate for small, short-period Kepler planet candidates. Since planetary transits should be largely achromatic when observed at different wavelengths (excluding the small color changes due to stellar limb darkening), we use the observed transit color to identify candidates as either false positives (e.g., a blend with a stellar eclipsing binary either in the background/foreground or bound to the target star) or validated planets. Our results include the identification of KOI 225.01 and KOI 1187.01 as false positives and the tentative validation of KOI 420.01 and KOI 526.01 as planets. The probability of identifying two false positives out of a sample of four targets is less than 1%, assuming an overall false positive rate for Kepler planet candidates of 10% (as estimated by Morton & Johnson 2011). Therefore, these results suggest a higher false positive rate for the small, short-period Kepler planet candidates than has been theoretically predicted by other studies which consider the Kepler planet candidate sample as a whole. Furthermore, our results are consistent with a recent Doppler study of short-period giant Kepler planet candidates (Santerne et al. 2012). We also investigate how the false positive rate for our sample varies with different planetary and stellar properties. Our results suggest that the false positive rate varies significantly with orbital period and is largest at the shortest orbital periods (P < 3 days), where there is a corresponding rise in the number of detached eclipsing binary stars... (truncated)Comment: 13 pages, 12 figures, 3 tables; revised for MNRA