Detection of Atherosis in Preeclamptic Placentas: Comparison of Two Gross Sampling Protocols

2005 ◽  
Vol 8 (1) ◽  
pp. 61-65 ◽  
Author(s):  
Norman Walford ◽  
Kyaw Htun ◽  
Meenakshi Akhilesh
Keyword(s):  
Detection Rate ◽  
Current Practice ◽  
High Detection Rate ◽  
Detection Rates ◽  
Sampling Protocols ◽  
En Face ◽  
High Detection ◽  
Vascular Compromise ◽  
Flat Membrane ◽  
Criteria For Diagnosis

Two standardized gross sampling protocols were compared with the intention of maximizing the histologic detection rate of atherosis in at-risk (i.e., preeclamptic) placentas. The first, 4-block, protocol was designed to be broadly representative of good current practice (central, edge, en face shave, and membrane roll blocks). A second, 5-block, protocol incorporated all of protocol 1 with the addition of a block composed of multiple flat membrane leaves stacked and sectioned 5 times at 200-μm intervals. Data were available on the first protocol from 80 consecutive accessioned cases of singleton preeclamptic placentas and on the second protocol from 40 cases. Criteria for diagnosis for atherosis were relatively rigorous and excluded “burnt-out” fibrinoid lesions in which foam cells were not positively identified. With the first protocol, atherosis was detected in 30 of 80 (37.5%) of placentas studied. With the second protocol, atherosis was detected in 25 of 40 (62.5%) of placentas studied. This increase was related to a high detection rate of 50% in the flat membrane stack block. Evaluation of the more traditional forms of block produced atherosis detection rates of 2.5% for central full-thickness blocks, 14% for edge blocks, 10% for en face shave blocks, and 25% for membrane rolls. The flat membrane stack was found to be the single most sensitive block for detection of atherosis. When used in conjunction with traditional blocking techniques, it offers significantly increased reliability for detection of atherosis in placentas when maternal vascular compromise is suspected.

Application of Bayesian Forecasting to Change Detection and Prognosis of Gas Turbine Performance

2009 ◽  
Vol 132 (3) ◽  
Author(s):  
Holger Lipowsky ◽  
Stephan Staudacher ◽  
Michael Bauer ◽  
Klaus-Juergen Schmidt
Keyword(s):  
Change Detection ◽  
Probability Density ◽  
Alternative Model ◽  
Detection Rate ◽  
Bayesian Forecasting ◽  
False Detection Rate ◽  
False Detection ◽  
High Detection Rate ◽  
Detection Rates ◽  
High Detection

The performance of gas turbines degrades over time due to deterioration mechanisms and single fault events. While deterioration mechanisms occur gradually, single fault events are characterized by occurring accidentally. In the case of single events, abrupt changes in the engine parameters are expected. Identifying these changes as soon as possible is referred to as detection. State-of-the-art detection algorithms are based on expert systems, neural networks, special filters, or fuzzy logic. This paper presents a novel detection technique, which is based on Bayesian forecasting and dynamic linear models (DLMs). Bayesian forecasting enables the calculation of conditional probabilities, whereas DLMs are a mathematical tool for time series analysis. The combination of the two methods can be used to calculate probability density functions prior to the next observation, or the so called forecast distributions. The change detection is carried out by comparing the current model with an alternative model, where the mean value is shifted by a prescribed offset. If the forecast distribution of the alternative model better fits the actual observation, a potential change is detected. To determine whether the respective observation is a single outlier or the first observation of a significant change, a special logic is developed. In addition to change detection, the proposed technique has the ability to perform a prognosis of measurement values. The developed method was run through an extensive test program. Detection rates >92% have been achieved for changed heights, as small as 1.5 times the standard deviation of the observed signal (sigma). For changed heights greater than 2 sigma, the detection rates have proven to be 100%. It could also be shown that a high detection rate is gained by a high false detection rate (∼2%). An optimum must be chosen between a high detection rate and a low false detection rate, by choosing an appropriate uncertainty limit for the detection. Increasing the uncertainty limit decreases both detection rate and false detection rate. In terms of prognostic abilities, the proposed technique not only estimates the point of time of a potential limit exceedance of respective parameters, but also calculates confidence bounds, as well as probability density and cumulative distribution functions for the prognosis. The conflictive requirements of a high degree of smoothing and a quick reaction to changes are fulfilled in parallel by combining two different detection conditions.

scholarly journals [18F]-JK-PSMA-7 PET/CT Under Androgen Deprivation Therapy in Advanced Prostate Cancer

2020 ◽  
Author(s):  
Felix Dietlein ◽  
Peter Mueller ◽  
Carsten Kobe ◽  
Heike Endepols ◽  
Melanie Hohberg ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Androgen Deprivation Therapy ◽  
Detection Rate ◽  
Androgen Deprivation ◽  
High Detection Rate ◽  
Detection Rates ◽  
Pet Ct ◽  
Significant Difference ◽  
High Detection

Abstract Purpose PSMA imaging is frequently used for monitoring of androgen deprivation therapy (ADT) in prostate cancer. In a previous study, [18F]-JK-PSMA-7 exhibited favorable properties for tumor localization after biochemical recurrence. In this retrospective study, we evaluated the performance of [18F]-JK-PSMA-7 under ADT. Procedures We examined the performance of [18F]-JK-PSMA-7 in 70 patients (first cohort) with increasing or detectable PSA values under ADT (PSA < 2 ng/ml for 21/70 patients). We further analyzed 58 independent patients with PSA levels < 2 ng/ml under ADT, who were imaged with [68Ga]PSMA-11 or [18F]DCFPyL (second cohort). Finally, we compared detection rates between [18F]-JK-PSMA-7, [68Ga]PSMA-11, and [18F]DCFPyL. Results In the first cohort, we detected [18F]-JK-PSMA-7-positive lesions in 63/70 patients. In patients with PSA levels ≥ 2 ng/ml, the detection rate was 100 % (49/49). In patients with PSA < 2 ng/ml, the detection rate was significantly lower (66.7 %, 14/21, p = 9.7 × 10−5) and dropped from 85.7 % (12/14, PSA levels between 0.3 and 2.0 ng/ml) to 28.6 % (2/7) for PSA levels < 0.3 ng/ml (p = 1.73 × 10−2). In the second cohort (PSA < 2 ng/ml), the detection rate was 79.3 % (46/58) for [68Ga]PSMA-11 or [18F]DCFPyL. Again, the detection rate was significantly higher (p = 1.1 × 10−2) for patients with PSA levels between 0.3 and 2.0 ng/ml (87.0 %, 40/46) relative to those with PSA levels < 0.3 ng/ml (50 %, 6/12). No significant difference was found between [18F]-JK-PSMA-7 and [68Ga]PSMA-11 or [18F]DCFPyL in patients with PSA levels < 2 ng/ml (p = 0.4295). Conclusion [18F]-JK-PSMA-7 PET showed a high detection rate in patients with PSA levels ≥ 0.3 ng/ml under ADT. The lower PSA threshold of 0.3 ng/ml for high detection rates was consistent across the three PSMA ligands. Thus, PSMA imaging is suitable for clinical follow-up of patients with increasing PSA levels under ADT.

A Comparative Review of Various Machine Learning Approaches for Improving the Performance of Stego Anomaly Detection

2018 ◽  
pp. 351-371 ◽  
Author(s):  
Hemalatha Jeyaprakash ◽  
KavithaDevi M. K. ◽  
Geetha S.
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
Detection Rate ◽  
High Dimensional ◽  
Learning Approaches ◽  
Learning Tools ◽  
High Detection Rate ◽  
Comparative Review ◽  
High Detection

In recent years, steganalyzers are intelligently detecting the stego images with high detection rate using high dimensional cover representation. And so the steganographers are working towards this issue to protect the cover element dependency and to protect the detection of hiding secret messages. Any steganalysis algorithm may achieve its success in two ways: 1) extracting the most sensitive features to expose the footprints of message hiding; 2) designing or building an effective classifier engine to favorably detect the stego images through learning all the stego sensitive features. In this chapter, the authors improve the stego anomaly detection using the second approach. This chapter presents a comparative review of application of the machine learning tools for steganalysis problem and recommends the best classifier that produces a superior detection rate.

A Approach to Change Detection for HR Image

2014 ◽  
Vol 971-973 ◽  
pp. 1449-1453
Author(s):  
Zuo Wei Huang ◽  
Shu Guang Wu ◽  
Tao Xin Zhang
Keyword(s):  
Change Detection ◽  
Detection Rate ◽  
False Detection Rate ◽  
False Detection ◽  
High Detection Rate ◽  
High Detection ◽  
Self Adaptation ◽  
Ica Algorithm ◽  
Different Characteristics ◽  
Better Than

Hyperspectral remote sensing is the multi-dimensional information obtaining technology,which combines target detection and spectral imaging technology together, In order to accord with the condition of hyperspectral imagery，the paper developed an optimized ICA algorithm for change detection to describe the statistical distribution of the data. By processing these abundance maps, change of different classes of objects can be obtained..A approach is capable of self-adaptation, and can be applied to hyperspectral images with different characteristics. Experiment results demonstrate that the ICA-based hyperspectral change detection performs better than other traditional methods with a high detection rate and a low false detection rate.

scholarly journals Stroke Risk Analysis, a System With a High Detection Rate of Atrial Fibrillation in Stroke and Transient Ischemic Attack

Stroke ◽  
2020 ◽  
Vol 51 (1) ◽  
pp. 262-267 ◽  
Author(s):  
Meritxell Gomis ◽  
Antoni Dávalos ◽  
Francisco Purroy ◽  
Pere Cardona ◽  
Ana Rodríguez-Campello ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Risk Analysis ◽  
Transient Ischemic Attack ◽  
Detection Rate ◽  
Stroke Risk ◽  
High Detection Rate ◽  
High Detection ◽  
Ischemic Attack

THE DOUBLE PULSAR SYSTEM J0737–3039

2005 ◽  
Vol 20 (29) ◽  
pp. 7035-7044 ◽  
Author(s):  
D. R. LORIMER
Keyword(s):  
General Relativity ◽  
Neutron Star ◽  
Gravitational Wave ◽  
Detection Rate ◽  
Order Effects ◽  
Gravitational Wave Detector ◽  
High Detection Rate ◽  
Wave Detector ◽  
High Detection ◽  
Order Of Magnitude

The double pulsar system J0737 – 3039 – a 22.7 ms pulsar in a compact 2.4 hr orbit about a 2.7 s pulsar was one of the long-awaited "holy grails" of pulsar astronomy. After only two years of timing, the system is close to surpassing the original Hulse-Taylor binary as a test of general relativity. On-going timing should soon reveal second-order effects in the post-Newtonian parameters. In addition, the observed interactions of the radio beams of the two pulsars provide a unique laboratory for probing neutron star magnetospheres and relativistic winds. Finally, a revised estimate of the cosmic rate of double neutron star mergers including J0737 – 3039 boosts previous estimates by an order of magnitude and suggests a high detection rate for the advanced LIGO gravitational wave detector.

High detection rate of clinically relevant genomic abnormalities in plasma cells enriched from patients with multiple myeloma

2012 ◽  
Vol 51 (11) ◽  
pp. 997-1006 ◽  
Author(s):  
Marian Stevens-Kroef ◽  
Daniel Olde Weghuis ◽  
Sandra Croockewit ◽  
Leo Derksen ◽  
Jeroen Hooijer ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Detection Rate ◽  
Plasma Cells ◽  
High Detection Rate ◽  
High Detection
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