Journal Articles

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884

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Author: search.filters.author.Chandrika, B.K.

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    Visually lossless coder for volumetric MRI and CT image data using wavelet transform
    (Inderscience Publishers, 2017) Chandrika, B.K.; Aparna., P.; Sumam David, S.S.
    Medical imaging modalities produce large volume of digital data each day in modern healthcare. Several techniques have been proposed for volumetric medical image data compression. In this paper, we present a novel wavelet-based visually lossless coding scheme for the compression of volumetric magnetic resonance imaging (MRI) and computed tomography (CT) images. A visual model is incorporated in the coder to identify and measure visually irrelevant information. Performance of the compression scheme is further improved by eliminating the slice redundancy. The obtained results show better compression ratio compared to results obtained with pixel-based visually lossless compression technique, without any degradation in visual quality. We compared the performance of proposed technique with standard state of the art compression codecs such as joint photographic experts group-lossless (JPEG-LS), JPEG-2000, JPEG-3D, H.264/MPEG-4 AVC, differential pulse code modulation (DPCM) and medical image lossless compression (MILC). Results show better compression ratio over that of standard lossless compression schemes without any perceivable distortion. © 2017 Inderscience Enterprises Ltd.
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    Perceptually lossless coder for volumetric medical image data
    (Academic Press Inc. apjcs@harcourt.com, 2017) Chandrika, B.K.; Aparna., P.; Sumam David, S.S.
    With the development of modern imaging techniques, every medical examination would result in a huge volume of image data. Analysis, storage and/or transmission of these data demands high compression without any loss of diagnostically significant data. Although, various 3-D compression techniques have been proposed, they have not been able to meet the current requirements. This paper proposes a novel method to compress 3-D medical images based on human vision model to remove visually insignificant information. The block matching algorithm applied to exploit the anatomical symmetry remove the spatial redundancies. The results obtained are compared with those of lossless compression techniques. The results show better compression without any degradation in visual quality. The rate-distortion performance of the proposed coders is compared with that of the state-of-the-art lossy coders. The subjective evaluation performed by the medical experts confirms that the visual quality of the reconstructed image is excellent. © 2017
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    An Approach for Diagnostically Lossless Coding of Volumetric Medical Data Based on Wavelet and Just-Noticeable-Distortion Model
    (Taylor and Francis Ltd., 2023) Chandrika, B.K.; Aparna., P.; Sumam David, S.
    This paper explores a technique for visually/diagnostically lossless coding in the wavelet domain to effectively compress the three-dimensional medical image data. The quantisation module based on Just Noticeable Distortion (JND) for wavelets guarantees the visual quality in the reconstructed data. This method has been further extended to present the Volume of Interest (VOI) based technique that enables to preserve the quality of the diagnostically significant VOI region. The proposed method tested on several datasets outperforms the state-of-the-art methods. Apart from the conventional quality metric, Human Visual System (HVS) based quality metrics are also used to evaluate the visual quality of the reconstructed image. A subjective and objective evaluation carried out for VOI based coder shows that the quality-compression needs of the medical community are well addressed. © 2023 IETE.