Novel Method for More Efficient Optimizing the Knowledge-Based Planning: Specific Voxels of each Structure Influenced by Dominant Beamlets (SVSIDB)

There is a huge problem and time-consuming computation to optimize the IMRT treatment plan. Extracting the optimized plan from the predicted 3D3 so-called optimizing the KBP is also involved in this challenge. Some algorithms and methods have been presented for clustering and down-sampling the voxels to make the problem smaller, in recent years. In the current research, a novel down-sampling method is presented for optimizing the knowledge-based planning more efficiently. The concept of SVSIDB and corresponding down-sampling algorithm are proposed under title of SMP-2. The algorithm has been run on the data of 30 patients from the Open-KBP dataset. For each patient, there are 19 sets of dose prediction data in this dataset. Therefore, a total of 570 KBP-optimizing problems have been solved by applying the QuadLin model in the CVX framework. Resulted plans are evaluated and compared regarding two main fields which are the quality of the treatment plan as well as the computation efficiency. Solve time is the evaluation criteria for the latter field i.e. computation efficiency. The results of the current study indicated a remarkable improvement in the computation efficiency. Accordingly, the proposed method, SMP-2, reduced the average solving time by 46% in comparison to the full-data QuadLin model. The results also show an up to 53% reduction in solve time along with up to 22% improvement in clinical criteria compared to the previous research. Evaluation of the research results indicated that the SVSIDB has not only reduced the solve time but also improved the quality of the treatment plans. This is a remarkable achievement of the proposed model compared to the previous research and confirmed the significant effectiveness of the SVSIDB method which has the potential of even more improvement of the computation efficiency.Comment: Keywords: Computing Efficiency; Voxels Down-Sampling; Radiotherapy Treatment Planning; Clustering. arXiv admin note: text overlap with arXiv:2206.0583

Exercise therapy, quality of life, and activities of daily living in patients with Parkinson disease: a small scale quasi-randomised trial

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Application Of Multi-Criteria Decision Making Approaches In Prioritizing Highway Bridges Inventory For Seismic Retrofitting

Many of the bridges are old or were designed without seismic design considerations in areas with potential earthquake hazard. These bridges are vulnerable from even moderate earthquakes and require to be retrofitted in some degree for reducing the future social and economic costs. Besides, the process of seismic retrofitting is extremely costly and time consuming moreover the constraint in resources prevents the retrofitting of all the existing bridges simultaneously. Hence, the bridges must be prioritized with simultaneous consideration of multiple criteria including technical and socioeconomic issues. This study intends to identify the major criteria and their weight for evaluation of highway bridges and providing an effective technique to prioritize the bridges. Suggested criteria include structural vulnerability, seismic hazard, anticipated service life, average daily traffic, interface with other lifelines, alternative routes and bridge importance. To assess the weight of criteria the Analytic Hierarchy Process (AHP) technique is carried out. Since the problem involving a large number of alternatives (bridges) and multiple criteria, VIKOR (VlseKriterijumskaOptimizacija I KompromisnoResenje) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) methods as Multi-Criteria Decision-Making (MCDM) model are applied for prioritizing of bridges. These methods reduce multitude alternative performances into a single value and prioritize the alternatives (bridges) based on their ranking score

Comparison of Performance of Bloom with Bloomless and Sparse-bloom Near-isohybrids of Sorghum

Agronom