A Bayesian random partition model for sequential refinement and coagulation

Biometrics ◽  
2019 ◽  
Vol 75 (3) ◽  
pp. 988-999
Author(s):  
Carlos Tadeu Pagani Zanini ◽  
Peter Müller ◽  
Yuan Ji ◽  
Fernando A. Quintana
Keyword(s):  
Random Partition ◽  
Partition Model

scholarly journals Y-90 SIRT: evaluation of TCP variation across dosimetric models

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Benjamin J. Van ◽  
Yuni K. Dewaraja ◽  
Mamadou L. Sangogo ◽  
Justin K. Mikell
Keyword(s):  
Standard Model ◽  
Volume Fraction ◽  
Liver Tumors ◽  
Package Insert ◽  
Absorbed Dose ◽  
Tumor Control ◽  
Partition Model ◽  
Pet Ct ◽  
The Standard Model ◽  
Biological Outcomes

Abstract Introduction Much progress has been made in implementing selective internal radiation therapy (SIRT) as a viable treatment option for hepatic malignancies. However, there is still much need for improved options for calculating the amount of activity to be administered. To make advances towards this goal, this study examines the relationship between predicted biological outcomes of liver tumors via tumor control probabilities (TCP) and parenchyma via normal tissue complication probabilities (NTCP) given variations in absorbed dose prescription methodologies. Methods Thirty-nine glass microsphere treatments in 35 patients with hepatocellular carcinoma or metastatic liver disease were analyzed using 99mTc-MAA SPECT/CT and 90Y PET/CT scans. Predicted biological outcomes corresponding to the single compartment (standard) model and multi-compartment (partition) dosimetry model were compared using our previously derived TCP dose-response curves over a range of 80–150 Gy prescribed absorbed dose to the perfused volume, recommended in the package insert for glass microspheres. Retrospective planning dosimetry was performed on the MAA SPECT/CT; changes from the planned infused activity due to selection of absorbed dose level and dosimetry model (standard or partition) were used to scale absorbed doses reported from 90Y PET/CT including liver parenchyma and lesions (N = 120) > 2 ml. A parameterized charting system was developed across all potential prescription options to enable a clear relationship between standard prescription vs. the partition model-based prescription. Using a previously proposed NTCP model, the change in prescribed dose from a standard model prescription of 120 Gy to the perfused volume to a 15% NTCP prescription to the normal liver was explored. Results Average TCP predictions for the partition model compared with the standard model varied from a 13% decrease to a 32% increase when the prescribed dose was varied across the range of 80–150 Gy. In the parametrized chart comparing absorbed dose prescription ranges across the standard model and partition models, a line of equivalent absorbed dose to a tumor was identified. TCP predictions on a per lesion basis varied between a 26% decrease and a 81% increase for the most commonly chosen prescription options when comparing the partition model with the standard model. NTCP model was only applicable to a subset of patients because of the small volume fraction of the liver that was targeted in most cases. Conclusion Our retrospective analysis of patient imaging data shows that the choice of prescribed dose and which model to prescribe potentially contribute to a wide variation in average tumor efficacy. Biological response data should be included as one factor when looking to improve patient care in the clinic. The use of parameterized charting, such as presented here, will help direct physicians when transitioning to newer prescription methods.

Reconstruction and estimation in the planted partition model

2014 ◽  
Vol 162 (3-4) ◽  
pp. 431-461 ◽  
Author(s):  
Elchanan Mossel ◽  
Joe Neeman ◽  
Allan Sly
Keyword(s):  
Partition Model

scholarly journals Visual tracking via random partition image hashing

2016 ◽  
Author(s):  
Mingyang Guan ◽  
Changyun Wen ◽  
Kwang-Yong Lim ◽  
Mao Shan ◽  
Paul Tan ◽  
...  
Keyword(s):  
Visual Tracking ◽  
Image Hashing ◽  
Random Partition

Random mosaics with cells of general topology

1996 ◽  
Vol 28 (02) ◽  
pp. 332
Author(s):  
Richard Cowan ◽  
Albert K. L. Tsang
Keyword(s):  
Euler Characteristic ◽  
Ergodic Theory ◽  
General Topology ◽  
Traditional Theory ◽  
Random Partition ◽  
Random Tessellation ◽  
Random Tessellations ◽  
Partition Process

This paper considers a structure, named a ‘random partition process’, which is a generalisation of a random tessellation. The cells, possibly multi-part and with holes, have a general topology summarised by the Euler characteristic. Vertices of all orders are allowed. Using the tools of ergodic theory, all of the formulae, from the traditional theory of random tessellations with convex cells, are generalised. Some motivating examples are given.

scholarly journals Selection of Best Test Cases using Support Vector Machine for ARPT

2019 ◽  
Vol 8 (3) ◽  
pp. 4265-4271
Keyword(s):  
Support Vector Machine ◽  
Software Testing ◽  
Support Vector ◽  
Test Cases ◽  
Testing Strategy ◽  
Random Partition ◽  
Code Coverage ◽  
Time Consumption ◽  
Branch Coverage ◽  
Selection Of

Software testing is an essential activity in software industries for quality assurance; subsequently, it can be effectively removing defects before software deployment. Mostly good software testing strategy is to accomplish the fundamental testing objective while solving the trade-offs between effectiveness and efficiency testing issues. Adaptive and Random Partition software Testing (ARPT) approach was a combination of Adaptive Testing (AT) and Random Partition Approach (RPT) used to test software effectively. It has two variants they are ARPT-1 and ARPT-2. In ARPT-1, AT was used to select a certain number of test cases and then RPT was used to select a number of test cases before returning to AT. In ARPT-2, AT was used to select the first m test cases and then switch to RPT for the remaining tests. The computational complexity for random partitioning in ARPT was solved by cluster the test cases using a different clustering algorithm. The parameters of ARPT-1 and ARPT-2 needs to be estimated for different software, it leads to high computation overhead and time consumption. It was solved by Improvised BAT optimization algorithms and this approach is named as Optimized ARPT1 (OARPT1) and OARPT2. By using all test cases in OARPT will leads to high time consumption and computational overhead. In order to avoid this problem, OARPT1 with Support Vector Machine (OARPT1-SVM) and OARPT2- SVM are introduced in this paper. The SVM is used for selection of best test cases for OARPT-1 and OARPT-2 testing strategy. The SVM constructs hyper plane in a multi-dimensional space which is used to separate test cases which have high code and branch coverage and test cases which have low code and branch coverage. Thus, the SVM selects the best test cases for OARPT-1 and OARPT-2. The selected test cases are used in OARPT-1 and OARPT-2 to test software. In the experiment, three different software is used to prove the effectiveness of proposed OARPT1- SVM and OARPT2-SVM testing strategies in terms of time consumption, defect detection efficiency, branch coverage and code coverage.

NUMERICAL STUDY OF THE 3-COLOR PROBLEM ON CUBIC LATTICE BY A METHOD OF RANDOM PARTITION FUNCTIONS

1994 ◽  
Vol 08 (07) ◽  
pp. 439-443
Author(s):  
A. V. BAKAEV ◽  
V. I. KABANOVICH
Keyword(s):  
Numerical Study ◽  
Stochastic Method ◽  
Partition Functions ◽  
Random Partition ◽  
Spin Models ◽  
Cubic Lattice ◽  
Color Problem ◽  
Lattice Spin ◽  
Finite Lattices ◽  
Lattice Spin Models

We propose a stochastic method for computing partition functions of models which can be stated as lattice spin models. The method admits averaging over independent realizations, thus is well suited for simulating models on finite lattices. We apply this method to the 3-color problem on cubic map.

Heat transfer analysis of waxy crude oil under a new wide phase change partition model

2019 ◽  
Vol 76 (12) ◽  
pp. 991-1005
Author(s):  
Ying Xu ◽  
Xin Nie ◽  
Zhonghua Dai ◽  
Xiaoyan Liu ◽  
Yang Liu ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Crude Oil ◽  
Phase Change ◽  
Heat Transfer Analysis ◽  
Waxy Crude Oil ◽  
Partition Model ◽  
Waxy Crude
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