Content Based Medical Image Coding with Fuzzy Level Set Segmentation Algorithm

What is it about?

Advances in digital medical imaging technologies have resulted in substantial increase in the size of datasets, as a result of improvement in spatial and temporal resolution. In order to reduce the storage cost, diagnostic analysis cost and transmission time without significant reduction of the image quality, a state of the art image compression technique is required. Content based coding is therefore capable of delivering high reconstruction quality over user-specified spatial regions in a limited time, compared to compression of the entire image. Further, CBC coding provides an excellent trade-off between image quality and compression ratio. In this paper a content based compression technique is proposed. The proposed procedure when applied on Computed Tomography (CT) liver image yields significantly better compression rates without loss in the originality of ROI

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Why is it important?

CBC coding provides an excellent trade-off between image quality and compression ratio

Perspectives