Takafumi Katayama

Cost-effectiveness of intensive insulin therapy for type 2 diabetes: a 10-year follow-up of the Kumamoto study

To evaluate the cost and effectiveness of intensive insulin therapy for type 2 diabetes on the prevention of diabetes complications in Japan, we performed economic evaluation based on a randomized controlled trial. A total of 110 patients with type 2 diabetes were randomly assigned into two groups, a multiple insulin injection therapy (MIT) group or a conventional insulin injection therapy (CIT) group, and were followed-up for 10 years. Economic evaluation (cost-consequences analysis) was applied to evaluate both health and economic outcomes. As outcome measures for effectiveness of intensive insulin therapy, the frequency of complications, such as retinopathy, nephropathy, neuropathy, macrovascular event, and diabetes-related death, was used. For estimating costs, a viewpoint of the payer (the National Health Insurance) was adopted. Direct medical costs associated with diabetes care during 10 years were calculated and evaluated. In a base case analysis, all costs were discounted to the present value at an annual rate of 3%. Sensitivity analyses were carried out to assess the robustness of the results to changes in the values of important variables. MIT reduced the relative risk in the progression of retinopathy by 67%, photocoagulation by 77%, progression of nephropathy by 66%, albuminuria by 100% and clinical neuropathy by 64%, relative to CIT. Moreover, MIT prolonged the period in which patients were free of complications, including 2.0 years for progression of retinopathy (P<0.0001), 0.3 years for photocoagulation (P<0.05), 1.5 years for progression of nephropathy (P<0.01) and 2.2 years for clinical neuropathy (P<0.0001). The total cost (discounted at 3%) per patient during the 10-year period for each group was

Early depth determination algorithm for enhancement layer intra coding of SHVC

30310 and 31525, respectively. The reduction of total costs in MIT over CIT was mainly due to reduced costs for management of diabetic complications. Our results show that MIT is more beneficial than CIT in both cost and effectiveness. Therefore, MIT is recommended for the treatment of type 2 diabetic patients who require insulin therapy as early as possible from the perspective of both patients and health policy.

Low complexity algorithm for inter-layer residual prediction of H.264/SVC

In this paper, an improved low complexity algorithm for the scalable extension of the HEVC (SHVC) is proposed by using the information of rate-distortion cost (RD cost) of the coding unit at the co-located position in the base layer and the neighboring coding unit in the enhancement layer. The proposed algorithm in our previous work used an early determination of the depth decision by adaptively selecting an optimal threshold value on the basis of RD cost. However, the threshold value become a low accuracy value because RD cost and the coding unit depth in different resolutions depend on the quantization parameter. Therefore, the relationship of the quantization parameter in different resolutions is evaluated. Based on the evaluation results, an improved algorithm focused on the complexity reduction of the enhancement layer is proposed. The proposed algorithm is evaluated by the reference software of SHVC(SHM6.0). The simulation results show that the proposed algorithm can achieve over 48% computation complexity reduction comparing to the original SHVC algorithm.

Low-complexity intra coding algorithm in enhancement layer for SHVC

The inter-layer residual prediction mode can increase the coding efficiency as well as the computation complexity. This paper presents a low complexity algorithm for inter-layer residual prediction of H.264/SVC. Proposed two-step algorithm focuses on the reduction of the candidate modes by making use of the correlations of the encoding cost between the base layer and enhancement layers. In the first step, the ordinary routine of rate-distortion optimization (RDO) for H.264/AVC is performed and a temporary best mode (TBM) is selected. Then, in the second step the encoding cost of the TBM and the candidate modes in the enhancement layer are compared to determine the redundant coding modes from all the candidate modes. The experiment results show that proposed algorithm can considerably reduce redundant computation complexity with almost no coding efficiency loss.

Health economics of care for patients with cancer and intractable disease in Japan.

In this paper, we propose an improved low complexity algorithm for the scalable extension of the HEVC (SHVC) using the information of Rate-Distortion cost and the coding unit (CU) size in the base layer. The proposed algorithm is used for inter layer reference prediction (ILRP) which is defined as a new mode in SHVC. Firstly, the relationship between of the different resolutions is evaluated when using ILRP mode. Next, based on the evaluation results, an improved algorithm focused on the complexity reduction of the enhancement layer is proposed. The proposed algorithm is evaluated by the reference software of SHVC. The simulation results show that the proposed algorithm can achieve over 60% computation complexity reduction comparing to the original SHVC algorithm.

Hardware implementation-oriented fast intra-coding based on downsampling information for HEVC

Abstract Concern about the economic aspect of cancer care is increasing. However, economic evaluations for cancer care are deficient in a number of areas, despite recent important contributions. To generate better evidence for economic evaluation of care for patients with cancer and intractable disease, the recent trends and problems with economic evaluations in these areas in Japan are examined. Several examples of economic evaluations, such as those concerned with bone marrow transplantation for leukemias, breast-conserving treatment for early breast cancer, and antiemetic treatment for patients receiving cancer chemotherapy, showed substantial possibilities for evaluating value for money in health care with a view to establishing an effective and efficient health care system.

Boundary correlation-based intracoding for SHVC algorithm and its efficient VLSI architecture

This paper proposes a downsampling information-based intra-coding scheme which consists of two parts, preprocessing stage and fast intra-coding stage. Three downsampling information-based fast decision algorithms are proposed in fast intra-coding stage. Moreover, a parallelized architecture for the proposed fast intra-coding scheme is proposed. The preprocessed downsampling stage can be executed with intra-coding stage in parallel. The proposed architecture fully makes use of this feature to improve the throughput and fragment data dependency. Experimental results demonstrate that the proposed algorithms achieves on average 60.4% reduction in encoding time with negligible coding efficiency loss, compared with original HEVC.

A Coding Efficiency Improvement Algorithm for Future Video Coding

Scalable high-efficiency video coding (SHVC) can provide variable video quality according to terminal devices. However, a computational complexity of SHVC is increased by introducing new techniques based on high-efficiency video coding (HEVC). In this paper, a hardware-oriented low complexity algorithm is proposed for the reference software of SHVC (SHM11.0). In our proposed algorithm, an optimal coding unit depth is determined by analyzing the boundary correlation in a coding tree unit before encoding starts. Simulation results show that the proposed algorithm can achieve over 62% computation complexity reduction comparing to the original SHM11.0. Compared with other related work, over 11% time saving has been achieved without PSNR loss. Moreover, to confirm the efficacy of the proposed algorithm, a hardware architecture is designed targeting on the CU depth decision algorithm. Synthesis results show that the hardware cost is about 1.8K gate and achieve a scalable working clock frequency in the case of FPGA (CycloneV) implementation.

Reference frame selection algorithm of HEVC encoder for low power video device

Motion estimation is critical in motion coding. However, the fixed pattern of search center decision method in HEVC is lack of precision. Taking advantage of the surrounding coding unit information, a universal motion vector prediction framework is presented to improve the coding efficiency in HEVC. The proposed framework is composed of two parts: motion vector prediction (MVP) and search range (SR) selection. Firstly, a novel motion vector prediction (NMVP) method is presented to improve the coding efficiency. Secondly, an adaptive search range selection (ASRS) method is developed to reduce the coding complexity in motion estimation. The simulation results demonstrate that the overall bitrate can be reduced by 5.49% on average, up to 9.18% compared with HEVC reference software.

Real-time architecture for inter-layer prediction of H.264/SVC

Modern video applications on mobile devices use higher resolutions and frame rates in order to offer better visual quality. Therefore, the power consumption reduction of the decoder in the mobile device is more challenging. In this paper, the reference frames selection algorithm of HEVC encoder for power consumption reduction on the decoder side is proposed. In particular, the power consumption of decoder for random access mode is significant compared with other coding mode. Firstly, the evaluation result show that when the number of group of picture and reference frames are varied on some conditions in random access mode. Next, based on the evaluation results, the proposed algorithm adaptively select the optimal number of reference frames in terms of the relationship of the prediction mode, coding unit size. The proposed algorithm is evaluated by the reference software of HEVC. The simulation results show that the proposed algorithm can reduce over 40% of the reference frames comparing to the original HEVC algorithm.