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In the present study, we aimed to assess the comparative efficacy of low-molecular-weight heparin (LMWH) in combination with low-dose aspirin for the management of recurrent miscarriage and scrutinize alterations in coagulation function following such treatment. A retrospective analysis was conducted on clinical data obtained from 97 patients with recurrent miscarriage treated at our institution from January 2019 to June 2020. Patients were categorized into either the study or control groups based on the administration of LMWH. The control group comprised 48 patients treated solely with aspirin, while the study group included 49 patients treated with both LMWH and aspirin. Comparative evaluations between the two groups encompassed pregnancy outcomes, coagulation function, adverse reactions, and blood loss during delivery. Results revealed a higher term birth rate in the study group (83.67%) compared to the control group (50%). Post-treatment, the study group exhibited lower prothrombin time, plasminogen activator inhibitor, and D-dimer levels than the control group. Moreover, the study group experienced fewer adverse reactions and reduced blood loss during delivery in comparison to the control group, demonstrating statistical significance (P < 0.05). The combination of LMWH and low-dose aspirin exhibited noteworthy application in the management of recurrent miscarriage. This therapeutic approach not only fostered the enhancement of coagulation function conducive to pregnancy but also diminished the incidence of adverse reactions observed with aspirin alone. [ABSTRACT FROM AUTHOR]

Radiomics is a technology that extracts a large number of quantitative features from high-throughput medical images and has become a focus of research. It can help in disease diagnosis, therapy planning, and prognosis evaluation through Big Data analysis algorithms. Radiomics technology can extract hundreds or even tens of thousands of quantifiable data features from medical images, which can no longer fit into the memory of one machine. Therefore, we propose a distributed correlation analysis algorithm (DFCA) based on a MapReduce distributed computing framework for breast ultrasound radiomics feature datasets. Each compute node will produce massive intermediate data while the DFCA calculates the Pearson correlation coefficient of radiomics features. With the increase of feature data and dimensions, the data transmission cost will be in a square growth. To reduce the cost, we propose a distributed correlation estimation algorithm (DFCEA) for radiomics features based on DFCA. The DFCEA algorithm estimates the Pearson correlation coefficient using an iterative method, which can further reduce the I/O cost. The experiment proved that our algorithms are more effective compared to the algorithms in the literature. [ABSTRACT FROM AUTHOR]

Contour extraction of image stacks is a basic task in medical modeling. The existing level-set methods usually suffer from some problems (e.g. serious errors around sharp features, incorrect split of topology and contour occlusions). This paper proposes a novel method of multi-constraint level-set evolution to avoid above-mentioned problems. Interpolation constraint and deviation constraint are added to evolution process in addition to existing constraints (such as edge points and areas). In order to prevent occlusions, it proposes a method of three-phase level-set evolution. The first phase obtains a rough contour according to selected edge points. The second phase applies an expanding LSE (level-set evolution). Missing edge points in the first phase are added when occlusions probably appear. In the third phase, occlusions are deleted and a refining evolution is implemented. As proved by final experiments, our method can steadily extract contours slice by slice when the shapes of previous contours (contours in the previous slice) are similar to current contours (contours in the current slice). Furthermore, there is no error propagation during the process of contour extraction. [ABSTRACT FROM AUTHOR]

Separation of the femur head and acetabulum is one of main difficulties in the diseased hip joint due to deformed shapes and extreme narrowness of the joint space. To improve the segmentation accuracy is the key point of existing automatic or semi-automatic segmentation methods. In this paper, we propose a new method to improve the accuracy of the segmented acetabulum using surface fitting techniques, which essentially consists of three parts: (1) design a surface iterative process to obtain an optimization surface; (2) change the ellipsoid fitting to two-phase quadric surface fitting; (3) bring in a normal matching method and an optimization region method to capture edge points for the fitting quadric surface. Furthermore, this paper cited vivo CT data sets of 40 actual patients (with 79 hip joints). Test results for these clinical cases show that: (1) the average error of the quadric surface fitting method is 2.3 (mm); (2) the accuracy ratio of automatically recognized contours is larger than 89.4%;(3) the error ratio of section contours is less than 10% for acetabulums without severe malformation and less than 30% for acetabulums with severe malformation. Compared with similar methods, the accuracy of our method, which is applied in a software system, is significantly enhanced. [ABSTRACT FROM AUTHOR]

ECT-spline curves for sequences of multiple knots are generated from different local ECT-systems via connection matrices. Under appropriate assumptions there is a basis of the space of ECT-splines consisting of functions having minimal compact supports, normalized to form a nonnegative partition of unity. The basic functions can be defined by generalized divided differences [24]. This definition reduces to the classical one in case of a Schoenberg space. Under suitable assumptions it leads to a recursive method for computing the ECT-B-splines that reduces to the de Boor–Mansion–Cox recursion in case of ordinary polynomial splines and to Lyche's recursion in case of Tchebycheff splines. For sequences of simple knots and connection matrices that are nonsingular, lower triangular and totally positive the spline weights are identified as Neville–Aitken weights of certain generalized interpolation problems. For multiple knots they are limits of Neville–Aitken weights. In many cases the spline weights can be computed easily by recurrence. Our approach covers the case of Bézier-ECT-splines as well. They are defined by different local ECT-systems on knot intervals of a finite partition of a compact interval [a,b] connected at inner knots all of multiplicities zero by full connection matrices A[i] that are nonsingular, lower triangular and totally positive. In case of ordinary polynomials of order n they reduce to the classical Bézier polynomials. We also present a recursive algorithm of de Boor type computing ECT-spline curves pointwise. Examples of polynomial and rational B-splines constructed from given knot sequences and given connection matrices are added. For some of them we give explicit formulas of the spline weights, for others we display the B-splines or the B-spline curves. [ABSTRACT FROM AUTHOR]

Abstract Cardinal ECT-spline curves are generated from one ECT-system of order n which is shifted by integer translations via one connection matrix. If this matrix is nonsingular, lower triangular and totally positive, there exists an ECT-B-spline function N 0 n ( x ) having minimal compact support [0, n ] whose integer translates span the cardinal ECT-spline space. This B-spline is computed explicitly piece by piece. Involved is the characteristic polynomial of a certain matrix which is the product of a matrix related to the connection matrix and of the generalized Taylor matrix of the basic ECT-system. This approach extends results for polynomial cardinal splines via connection matrices [6] to the more general setting of cardinal ECT-splines. The method is illustrated by two examples based on ECT-systems of rational functions with prescribed poles. Also, a Greens function involved is expressed explicitly as an ECT-B-splines series. [ABSTRACT FROM AUTHOR]