Two-threshold Algorithm Research Articles

Combining Donor-derived Cell-free DNA Fraction and Quantity to Detect Kidney Transplant Rejection Using Molecular Diagnoses and Histology as Confirmation.

Donor-derived cell-free DNA (dd-cfDNA) fraction and quantity have both been shown to be associated with allograft rejection. The present study compared the relative predictive power of each of these variables to the combination of the two, and developed an algorithm incorporating both variables to detect active rejection in renal allograft biopsies. The first 426 sequential indication biopsy samples collected from the Trifecta study ( ClinicalTrials.gov # NCT04239703) with microarray-derived gene expression and dd-cfDNA results were included. After exclusions to simulate intended clinical use, 367 samples were analyzed. Biopsies were assessed using the molecular microscope diagnostic system and histology (Banff 2019). Logistic regression analysis examined whether combining dd-cfDNA fraction and quantity adds predictive value to either alone. The first 149 sequential samples were used to develop a two-threshold algorithm and the next 218 to validate the algorithm. In regression, the combination of dd-cfDNA fraction and quantity was found to be significantly more predictive than either variable alone ( P = 0.009 and P < 0.0001). In the test set, the area under the receiver operating characteristic curve of the two-variable system was 0.88, and performance of the two-threshold algorithm showed a sensitivity of 83.1% and specificity of 81.0% for molecular diagnoses and a sensitivity of 73.5% and specificity of 80.8% for histology diagnoses. This prospective, biopsy-matched, multisite dd-cfDNA study in kidney transplant patients found that the combination of dd-cfDNA fraction and quantity was more powerful than either dd-cfDNA fraction or quantity alone and validated a novel two-threshold algorithm incorporating both variables.

427.4: Combining Donor Derived Cell-Free DNA Fraction and Quantity To Detect Kidney Transplant Rejection Using Molecular Diagnoses

Background: Donor-derived cell-free DNA (dd-cfDNA) fraction and quantity have both been shown to be associated with allograft rejection. The present study examined the relative predictive power of each of these variables to the combination of the two and developed an algorithm incorporating both variables to detect active rejection in renal allograft biopsies. Methods: The first 426 sequential indication biopsy samples collected from the Trifecta study (ClinicalTrials.gov # NCT04239703) with microarray-derived gene expression and dd-cfDNA results were included. After exclusions to simulate intended clinical use, 367 samples were analyzed. Biopsies were assessed using the Molecular Microscope Diagnostic System (MMDxTM) and histology (Banff 2019). Logistic regression analysis examined whether combining dd-cfDNA fraction and quantity adds predictive value to either alone. The first 149 sequential samples were used to develop a two-threshold algorithm, and the next 218 to validate the algorithm. Results: In regression, the combination of dd-cfDNA fraction and quantity was found to be significantly more predictive than either variable alone (p-value 0.009 and <0.0001). In the test set, the AUC of the two-variable system was 0.88 and performance of the two-threshold algorithm showed sensitivity 83.1% and specificity 81.0% using molecular diagnoses, and sensitivity 73.5% and specificity 80.8% using histology diagnoses. Conclusions: This prospective, biopsy-matched, multi-site dd-cfDNA study in kidney transplant patients found that the combination of dd-cfDNA fraction and quantity was more powerful than either dd-cfDNA fraction or quantity alone, and validated a novel two-threshold algorithm incorporating both variables.

Two-threshold algorithm for detecting point objects from stereo images

This paper considers various approaches to improving the detection performance of point dynamic objects by using stereo vision under conditions where complete joint processing of a stereo pair of images is impossible. An improved triangulation algorithm with double thresholding is implemented. The possibility of forming marks from epipolar lines is studied for the case of a priori known shooting geometry. The situation of stereo observation of a dynamic object by moving cameras is simulated. The dependence of the detection probability on the level of false alarms is obtained experimentally for the proposed algorithms using model data.

Data-Efficient Quickest Change Detection with On–Off Observation Control

In this article we extend Shiryaev's quickest change detection formulation by also accounting for the cost of observations used before the change point. The observation cost is captured through the average number of observations used in the detection process before the change occurs. The objective is to select an on–off observation control policy that decides whether or not to take a given observation, along with the stopping time at which the change is declared, to minimize the average detection delay, subject to constraints on both the probability of false alarm and the observation cost. By considering a Lagrangian relaxation of the constraint problem and using dynamic programming arguments, we obtain an a posteriori probability-based two-threshold algorithm that is a generalized version of the classical Shiryaev algorithm. We provide an asymptotic analysis of the two-threshold algorithm and show that the algorithm is asymptotically optimal—that is, the performance of the two-threshold algorithm approaches that of the Shiryaev algorithm—for a fixed observation cost, as the probability of false alarm goes to zero. We also show, using simulations, that the two-threshold algorithm has good observation cost-delay trade-off curves and provides significant reduction in observation cost compared to the naïve approach of fractional sampling, where samples are skipped randomly. Our analysis reveals that, for practical choices of constraints, the two thresholds can be set independent of each other: one based on the constraint of false alarm and another based on the observation cost constraint alone.

A new machine-vision-based approach for rapid dimensional inspection of an integrated circuit carrier tape

This study presents a rapid and reliable machine vision technique for measuring the principal features of interest in an integrated circuit carrier tape, namely the diameters of the circular sprocket perforations and centre hole, the width of the carrier tape, and the width and length of the centre cavity. In performing the measurement process, the quality of the image acquisition process is enhanced by using two auxiliary light sources to suppress the effects of natural variations in the environmental lighting conditions. Having acquired the image using a charge coupled device (CCD) camera, the features of interest are separated from the background region of the image using a two-threshold algorithm based on the Otsu threshold selection method. The edge of each feature is then extracted from the binary image using the Canny edge detection method. The dimensions of the circular features are obtained by fitting four right-angle triangles within the periphery of the extracted circular edge and then computing the circle diameter by taking the mean of the hypotenuse values of the four triangles as computed using the Pythagorean theorem.