Low power ASIC implementation of signed and unsigned wallace-tree with vedic multiplier using compressors

Prajwal, N.; Amaresha, S. K.; Yellampalli, Siva

doi:10.1109/smarttechcon.2017.8358471

Cited by 6 publications

(1 citation statement)

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“…Meanwhile, ASICs architecture is easier and faster to design since it only need fewer layers to fabricate and it contain fixed arrangement of integrated circuit for a particular use. Unfortunately, the obvious disadvantage of ASICs is no programmable resources are provided which not allow them to be reconstructed [9].…”

Section: Introductionmentioning

confidence: 99%

Algorithm development and hardware implementation for medical image compression system: a review

Ja’afar

Ahmad

2020

IJEECS

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<span>In the high-tech world, medical imaging is very important to diagnose and analyze illness inside human body. The increasing number of patients annually has continuously growth the amount of medical imaging data generated and directly causes a demand for data storage. Generally, medical images are rich with data, where these data are important for diagnosing purpose. However, some of the data represents redundant information and sometimes can be discarded. Thus, the research area on medical image compression dealing with three-dimensional (3-D) modalities need to be given more attention and exploration. The algorithm development using wavelet transform with software implementation are the famous topics explored among researchers, whilst fewer works have been done in utilizing curvelet transform in medical image compression. Along with that, very limited hardware implementation of 3-D medical image compression is discovered. In term of performance evaluation, most of the previous works conducted objective test compared with subjective test. To fill in this gap, medical image compression system will be reviewed, with the aim to identify the recent method used in medical image compression system. This paper thoroughly scrutinizes the recent advances in medical image compression mainly in terms of compression method, algorithm development with software and hardware implementations and performance evaluation. In conclusion, the overall picture of the medical image compression landscape, where most of the researchers more focused on algorithm development or software implementations without having the combination of software and hardware implementations.</span>

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Section: Introductionmentioning

confidence: 99%