IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> In this paper, the hardware design and FPGA implementation of a new efficient three-dimensional wavelet transform (3D-WT) algorithm for video compression is presented. This algorithm performs the temporal decomposition of a video sequence in a more efficient way than the classical 3D-WT algorithm. It exhibits lower memory demands and lower latencies for the compression and decompression processes than the classical one. This makes the addressed algorithm fits better for real-time video processing. The hardware design is based on the use of the transposed-form FIR filter structure which is hereby compared to the direct-form FIR filter. The former is found to exhibit less clock latency and less chip area utilization. The reference design is made scalable to any wavelet filter coefficients and to fit for any frame size. The chip area utilization is compared upon the FPGA implementation at different frame sizes. The designed system can be used for real-time video applications. <s> BIB001 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> This paper establishes a clear procedure for finite-length beam problem and convection-diffusion equation solution via Haar wavelet technique. An operational matrix of integration based on the Haar wavelet is established,and the procedure for applying the matrix to solve the differential equations is formulated. The fundamental idea of Haar wavelet method is to convert the differential equations into a group of algebra equations which involves a finite number of variables. Illustrative examples are given to demonstrate the fast and flexible of the method ,in the mean time,it is found that the trouble of Daubechies wavelets for solving the differential equations which need to calculate the correlation coefficients is avoided. The method can be used to deal with all the other differential and integral equations. <s> BIB002 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> This paper describes the design and implementation of 3D Haar wavelet transform (HWT) with transpose based computation and dynamic partial reconfiguration (DPR). As a result of the separability property of the multi-dimensional HWT, the proposed architecture has been implemented using a cascade of three N-point 1D HWT and two transpose memory for a 3D volume of N×N×N, suitable for 3D medical image compression. The proposed 3D HWT architectures were implemented on Xilinx Virtex-5 field programmable gate array (FPGA) using VHDL. An in-depth performance analysis and comparison has shown that DPR based implementation improves both speed and power consumption as well as reducing the hardware required for the system. <s> BIB003 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> This paper presents the design and implementation of three dimensional (3D) Haar wavelet transform (HWT) with transpose based computation and dynamic partial reconfiguration (DPR) mechanism on field programmable gate array (FPGA). Due to the separability property of the multi-dimensional HWT, the proposed architecture has been implemented using a cascade of three N-point one dimensional (1D) HWT and two transpose memories for a 3D volume of NxNxN suitable for real-time 3D medical imaging applications. These applications require continuous hardware servicing, hence DPR has been introduced. Two architectures were synthesised using VHDL and implemented on Xilinx Virtex-5 FPGAs. Experimental results and comparisons between different configurations using partial and non-partial reconfiguration processes and a detailed performance analysis of the area, power consumption and maximum frequency are analysed in this paper. <s> BIB004 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> In this paper, a PC-based fully-programmable medical ultrasound imaging system is presented where a high-performance graphics processing unit (GPU) is utilized to perform entire ultrasound processing. In the proposed architecture, ultrasound signal and image processing algorithms were divided into four modules and efficiently implemented on the NVIDA's Computer Unified Device Architecture (CUDA) platform (GeForce GTX285, NVIDA, Santa Clara, CA, USA). To evaluate the real-time performance of the proposed architecture, 64-channel, 128-scanline pre-beamformed radio-frequency (RF) data were captured with a commercial ultrasound machine (G40, Siemens Healthcare, Mountain View, CA, USA). The execution time was measured by examining the time stamp produced by a CIDA timer. For generating a 800×600 ultrasound B-mode image, it takes 18.32 ms for single-beam based ultrasound processing with the acquisition time of 19.7 ms. These results indicate that the GPU-based fully-programmable system architecture can support real-time ultrasound signal and image processing. <s> BIB005 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Tomographic imaging is an important disease diagnosis method. Specific image workstation is usually needed to process and visualize 3D medical image gathered from tomographic imaging equipments, because this process is computation intensive. Specific image workstation is large and expensive, which limits size and price of medical tomographic imaging system. To break these limits, this paper presents an embedded 3D medical image processing and visualization platform based on common dual-core processor. The proposed system parallelizes 3D medical image processing and visualization computing process to meet system real-time requirements. Main contributions of this paper includes analysis of core 3D medical data processing and visualization algorithm, program parallelization method analysis and implementation, system performance measurement and analysis. Program analysis results show that the proposed system fully utilizes hardware resource, and meets low-end and space-efficient medical imaging system requirements. <s> BIB006 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Applied digital signal processing courses offered at many universities do not normally include FPGA implementation of signal processing algorithms. This is due to the fact that students taking applied signal processing courses often are not familiar with FPGA programming languages and as a result FPGA implementation cannot be easily achieved in one-semester long applied digital signal processing courses. In this paper, we present an approach for making FPGA implementation easily achievable within one-semester long applied digital signal processing courses or within a relatively short design cycle time. Our approach is based on the LabVIEW FPGA Module which allows FPGA implementation to be achieved in a time-efficient manner via more intuitive graphical coding. An overview of our designed FPGA implementation approach covering typical laboratories that students encounter in applied digital signal processing courses is provided. <s> BIB007 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Telemedicine characterized by transmission of medical data and images between users is one of the emerging fields in medicine. Huge bandwidth is necessary for transmitting medical images over the internet. Resolution factor and number of images per diagnosis makes even the size of the images that belongs to a single patient to be very large in size. So there is an immense need for efficient compression techniques for use in compressing these medical images to decrease the storage space and efficiency of transfer the images over network for access to electronic patient records. This project summarizes the different transformation methods used in compression as compression is one of the techniques that reduces the amount of data needed for storage or transmission of information. This paper outlines the comparison of transformation methods such as DPCM (Differential Pulse Code Modulation), and prediction improved DPCM transformation step of compression and introduced a transformation which is efficient in both entropy reduction and computational complexity. A new method is then achieved by improving the perdiction model which is used in lossless JPEG. The prediction improved transformation increases the energy compaction of prediction model and as a result reduces entropy value of transformed image. After transforming the image Huffman encoding used to compress the image. As a result, the new algorithm shows a better efficiency for lossless compression of medical images, especially for online applications. The result is analyzed using MATLAB and implemented in hardware. <s> BIB008 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> The types of edges found in volumetric medical image data are typically smooth due to a phenomenon known as the Partial Volume Effect (PVE). These smooth edges are very different to the sharp edges typically found in real world images. Consequently, it is not appropriate to use conventional edge-based prediction schemes with medical image data. This paper proposes a novel edge-based prediction scheme that is optimised for use with the types of edges associated with the PVE. This technique exploits prior anatomical knowledge and the characteristics of the PVE regions to accurately predict unknown voxel data. Our experimental results show that the performance of this technique in edge regions is significantly better than previously documented edge-based prediction techniques. We also show that the inclusion of our proposed technique in a standard compression scheme improves the overall level of compression that can be achieved. <s> BIB009 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> This paper explores the pros and cons of reconfigurable computing in the form of FPGAs for high performance efficient computing. In particular, the paper presents the results of a comparative study between three different acceleration technologies, namely, Field Programmable Gate Arrays (FPGAs), Graphics Processor Units (GPUs), and IBM's Cell Broadband Engine (Cell BE), in the design and implementation of the widely-used Smith-Waterman pairwise sequence alignment algorithm, with general purpose processors as a base reference implementation. Comparison criteria include speed, energy consumption, and purchase and development costs. The study shows that FPGAs largely outperform all other implementation platforms on performance per watt criterion and perform better than all other platforms on performance per dollar criterion, although by a much smaller margin. Cell BE and GPU come second and third, respectively, on both performance per watt and performance per dollar criteria. In general, in order to outperform other technologies on performance per dollar criterion (using currently available hardware and development tools), FPGAs need to achieve at least two orders of magnitude speed-up compared to general-purpose processors and one order of magnitude speed-up compared to domain-specific technologies such as GPUs. <s> BIB010 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> This paper presents the design and implementation of distributed arithmetic (DA) architectures of three-dimensional (3-D) Discrete Wavelet Transform (DWT) with hybrid method for medical image compression. Due to the separability property of the multi-dimensional Haar and Daubechies, the proposed architecture has been implemented using a cascade of three N-point one-dimensional (1-D) Haar/Daubechies and two transpose memories for a 3-D volume of N×N×N, suitable for 3-D medical imaging applications. The architectures were synthesised using VHDL and G-code and implemented on field programmable gate array (FPGA) single board RIO (sbRIO-9632) with Spartan-3 (XC3S2000). Experimental results and an analysis of the area, power consumption, maximum frequency, latency, throughput as well as the subjective test are discussed in this paper. <s> BIB011 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> In this study, the performance of fractal-based coding algorithms such as standard fractal coding, quasi-lossless fractal coding and improved quasi-lossless fractal coding are evaluated by investigating their ability to compress magnetic resonance images (MRIs) based on compression ratio, peak signal-to-noise ratio and encoding time. For this purpose, MRI head scan test sets of 512 × 512 pixels have been used. A novel quasi-lossless fractal coding scheme, which preserves important feature-rich portions of the medical image, such as domain blocks and generates the remaining part of the image from it, has been proposed using fractal transformations. One of the biggest tasks in fractal image compression is reduction of encoding computation time. A machine learning-based model is used for reducing the encoding time and also for improving the performance of the quasi-lossless fractal coding scheme. The results show a better performance of improved quasi-lossless fractal compression method. The quasi-lossless and improved quasi-lossless fractal coding algorithms are found to outperform standard fractal coding thereby proving the possibility of using fractal-based image compression algorithms for medical image compression. The proposed algorithm allows significant reduction of encoding time and also improvement in the compression ratio. <s> BIB012 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Digital medical images are becoming even more widespread and used in a large variety of applications. Such images are often stored in local repositories and need to be transmitted/ received over the network. Therefore, data compression is an essential mechanism to adopt for improving the transmission time, as well as to optimize the required storage space. However, due to the clinical relevance of such data, lossless techniques are almost ever preferred, given that in such context it is not tolerated any loss of data. In this work, starting from the Medical Images Lossless Compression (MILC) algorithm, which enables the efficient coding of three-dimensional medical images achieving results comparable with the other state-of-art algorithms, we propose Parallel MILC, a fully parallelized version of that algorithm, which provides some attractive features with respect to MILC, especially in terms of execution speedup and scalability. In detail, we propose a novel design and implementation for the MILC algorithm, which is able to exploit the power and the capabilities of the parallel computing paradigm. It is important to point out that Parallel MILC can be executed on several heterogeneous device types supporting OpenCL (i.e. CPU, GPU, FPGA, etc.). The preliminary test results show a significant performance speedup of Parallel MILC compared to MILC. Consequently, the novel algorithm we propose provides MILC with strong scalability properties and complete transparency with respect the underlying hardware. <s> BIB013 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Healthcare delivery systems and Telemedical applications will undergo a dramatic change due to the developments in technologies, mobile computing, medical sensors and communication techniques. Medical Images taken as X-ray, Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), Ultra Sound and Computed Axial Tomography (CAT) will have medical information either in multi resolution or multidimensional form, this creates large amount of data. Due to this storage of data is become more complex. So compression is needed the one in image processing. Anyhow compression of medical data will leads to loss of information. In order to reduce this complexity, as well as preserve the medical data to be lossless for diagnostics purpose, this paper propose techniques Region growing and Modified Set Partition In Hierarchical Tree (MSPIHT) will enhance the performance of lossless compression and also enhance the Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) than the SPIHT coding method. <s> BIB014 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Fusion of multimodal medical images increases robustness and enhances accuracy in biomedical research and clinical diagnosis. It attracts much attention over the past decade. In this paper, an efficient multimodal medical image fusion approach based on compressive sensing is presented to fuse computed tomography (CT) and magnetic resonance imaging (MRI) images. The significant sparse coefficients of CT and MRI images are acquired via multi-scale discrete wavelet transform. A proposed weighted fusion rule is utilized to fuse the high frequency coefficients of the source medical images; while the pulse coupled neural networks (PCNN) fusion rule is exploited to fuse the low frequency coefficients. Random Gaussian matrix is used to encode and measure. The fused image is reconstructed via Compressive Sampling Matched Pursuit algorithm (CoSaMP). To show the efficiency of the proposed approach, several comparative experiments are conducted. The results reveal that the proposed approach achieves better fused image quality than the existing state-of-the-art methods. Furthermore, the novel fusion approach has the superiority of high stability, good flexibility and low time consumption. <s> BIB015 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Multimodal medical image fusion is an important task for the retrieval of complementary information from medical images. Shift sensitivity, lack of phase information and poor directionality of real valued wavelet transforms motivated us to use complex wavelet transform for fusion. We have used Daubechies complex wavelet transform (DCxWT) for image fusion which is approximately shift invariant and provides phase information. In the present work, we have proposed a new multimodal medical image fusion using DCxWT at multiple levels which is based on multiresolution principle. The proposed method fuses the complex wavelet coefficients of source images using maximum selection rule. Experiments have been performed over three different sets of multimodal medical images. The proposed fusion method is visually and quantitatively compared with wavelet domain (Dual tree complex wavelet transform (DTCWT), Lifting wavelet transform (LWT), Multiwavelet transform (MWT), Stationary wavelet transform (SWT)) and spatial domain (Principal component analysis (PCA), linear and sharp) image fusion methods. The proposed method is further compared with Contourlet transform (CT) and Nonsubsampled contourlet transform (NSCT) based image fusion methods. For comparison of the proposed method, we have used five fusion metrics, namely entropy, edge strength, standard deviation, fusion factor and fusion symmetry. Comparison results prove that performance of the proposed fusion method is better than any of the above existing fusion methods. Robustness of the proposed method is tested against Gaussian, salt & pepper and speckle noise and the plots of fusion metrics for different noise cases established the superiority of the proposed fusion method. <s> BIB016 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Abstract Speckle noise is an undesirable part of the ultrasound imaging process, since it can degrade the quality of ultrasound images and restrict the development of automatic diagnostic techniques for ultrasound images. Aiming at the problem of speckle noise, an improved de-speckling method for medical ultrasound images is proposed, which is based on the wavelet transformation and fast bilateral filter. According to the statistical properties of medical ultrasound image in the wavelet domain, an improved wavelet threshold function based on the universal wavelet threshold function is considered. The wavelet coefficients of noise-free signal and speckle noise are modeled as generalized Laplace distribution and Gaussian distribution, respectively. The Bayesian maximum a posteriori estimation is applied to obtain a new wavelet shrinkage algorithm. High-pass component speckle noise in the wavelet domain of ultrasound images is suppressed by the new shrinkage algorithm. Additionally, the coefficients of the low frequency signal in the wavelet domain are filtered by the fast bilateral filter, since the low-pass component of ultrasound images also contains some speckle noise. Compared with other de-speckling methods, experiments show that the proposed method has improved de-speckling performance for medical ultrasound images. It not only has better reduction performance than other methods but also can preserve image details such as the edge of lesions. <s> BIB017 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> The main aim of hierarchical lossless image compression is to improve accuracy, reduce the bit rate and improve the compression efficiency for the storage and transmission of the medical images while maintain an acceptable image quality for diagnosis purpose. The cost and limitation in bandwidth of wireless channels has made compression is necessity in today's era. In medical images, the contextual region is an area which contains an important information and must be transmitted without distortion. In this paper the selected region of the image is encoded with Adaptive Multiwavelet Transform AMWT) using Multi Dimensional Layered Zero Coding (MLZC). Experimental results shows that Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), Mean Structural Similarity Index (MSSIM) performance is high and Root Mean Square Error (RMSE), Mean Absolute Error (MAE) values are low, and moderate Compression Ratio (CR) at high Bits Per Pixel (BPP) when compared to the integer wavelet and multiwavelet transform. <s> BIB018 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Abstract Most of the existing image encryption techniques bear security risks for taking linear transform or suffer encryption data expansion for adopting nonlinear transformation directly. To overcome these difficulties, a novel image compression–encryption scheme is proposed by combining 2D compressive sensing with nonlinear fractional Mellin transform. In this scheme, the original image is measured by measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the nonlinear fractional Mellin transform. The measurement matrices are controlled by chaos map. The Newton Smoothed l 0 Norm ( NSL 0 ) algorithm is adopted to obtain the decryption image. Simulation results verify the validity and the reliability of this scheme. <s> BIB019 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> In this paper, an efficient field-programmable gate array (FPGA) implementation of the JPEG baseline image compression encoder is presented for wearable devices in health and wellness applications. In order to gain flexibility in developing FPGA-specific software and balance between real-time performance and resources utilization, A High Level Synthesis (HLS) tool is utilized in our system design. An optimized dataflow configuration with a padding scheme simplifies the timing control for data transfer. Our experiments with a system-on-chip multi-sensor system have verified our FPGA implementation with respect to real-time performance, computational efficiency, and FPGA resource utilization. <s> BIB020 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Long duration recordings of ECG signals require high compression ratios, in particular when storing on portable devices. Most of the ECG compression methods in literature are based on wavelet transform while only few of them rely on sparsity promotion models. In this paper we propose a novel ECG signal compression framework based on sparse representation using a set of ECG segments as natural basis. This approach exploits the signal regularity, i.e. the repetition of common patterns, in order to achieve high compression ratio (CR). We apply k-LiMapS as fine-tuned sparsity solver algorithm guaranteeing the required signal reconstruction quality PRDN (Normalized Percentage Root-mean-square Difference). Extensive experiments have been conducted on all the 48 records of MIT-BIH Arrhythmia Database and on some 24 hour records from the Long-Term ST Database. Direct comparisons of our method with several state-of-the-art ECG compression methods (namely ARLE, Rajoub's, SPIHT, TRE) prove its effectiveness. Our method achieves average performances that are two-three times higher than those obtained by the other assessed methods. In particular the compression ratio gap between our method and the others increases with growing PRDN. <s> BIB021 </s> IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW <s> INTRODUCTION <s> Abstract In this paper, a vector quantization algorithm is proposed for image compression. The proposed algorithm composed of three phases, initialization, iterative and finalization. The initialization phase based on Max–Min algorithm. The iterative phase is an adaptive LBG algorithm. The finalization frees the codebook from redundancy. The LBG adapted to locate the codebook points to line up across the boundary of the objects they represent. The algorithm testing results showed that images main features sustain the high compression ratios. The same algorithm is applicable to codebook bins to improve the quality for the areas that have fine details. <s> BIB022
Recently, the most widespread use of threedimensional (3-D) imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US) have generated massive amounts of volumetric data BIB011 - BIB013 . These have provided an impetus to the development of other applications  , BIB017 , in particular telemedicine and teleradiology BIB014 - BIB018 . In these fields, medical image compression is important since both efficient storage and transmission of data through high-bandwidth digital communication lines are of crucial importance BIB008 -  . Despite their advantages, most 3-D medical imaging algorithms are computationally intensive with matrix transformation as the most fundamental operation involved in the transform-based methods. Therefore, there is a real need for high-performance systems, whilst keeping architectures flexible to allow for quick upgradeability with real-time applications BIB004 , BIB019 . Moreover, in order to obtain efficient solutions for large medical data volume, an efficient implementation of these operations is of significant importance BIB009 , BIB012 . A reconfigurable hardware, in the form of field programmable gate arrays (FPGAs), appears as a viable building block in the construction of highperformance systems at an economical price BIB005 - BIB020 . Consequently, FPGAs are ideal candidates for their inherent advantages such as massive parallelism capabilities, multimillion gate counts, and special low-power packages BIB003 ,  . A-part from that, it surely understood digital signal processor (DSP) offer low data rates over the FPGAs processor. Meaning that, in high data throughput implementation such as image and video processing, FPGAs outperform over DSPs BIB007 , BIB010 . A close examination of the algorithms used in real-time medical image processing applications has revealed that many fundamental actions had involved matrix or vector operations BIB008 ,  , BIB021 , BIB022 . Most of these operations are matrix transforms that include fast Fourier transform (FFT), discrete wavelet transforms (DWT) BIB015 , and other recently developed transforms such as finite Radon, as well as curvelet and ridgelet transforms which are used in either two-dimensional (2-D) or three-dimensional (3-D) medical imaging. Unfortunately, computational complexity for the matrix transform algorithms is in the order of O (N × logN) for FFT to O (N 2 × J) for the curvelet transform (where N is the transform size and J is the maximum transform resolution level) which are computationally intensive for large size problems. Thus, efficient implementations for these operations are of interest not only because matrix transforms are important in their own right, but also because they automatically lead to efficient solutions to deal with massive medical volumes. Currently, 3-D transforms are being implemented with other methods, such as in a network of computers. Additionally, having a chip that is solely dedicated to this transform will give tremendous results BIB006 ,  . Despite its complexity, there has been an interest in 3-D DWT implementation on various platforms. Previous surveys have classified this research field into three categories: architecture development  , architecture with FPGAs implementation  - [39] , and finally architecture that has been implemented on other silicon platforms BIB001 . Referring to the existing implementation as reported by BIB001 , a huge gap stills remain for further research in exploiting reconfigurable computing for 3-D medical image compression in the form of two major limitations : 1. Medical image compression has not been intensively addressed in the existing 3-D DWT implementation. Only the Daubechies filter has been extensively used in several implementations  , BIB002 , BIB016 , whilst the Haar, Symlet, Coifflet and Biorthogonal filters remain available for further experimentation.