2016 IEEE International Conference on Big Data (Big Data) Comparison of Lossless Video and Image Compression Codecs for Medical Computed Tomography Datasets Vy Bui1,3, Lin-Ching Chang1, Dunling Li2, Li-Yueh Hsu3, Marcus Y. Chen3 1Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, DC, USA 2BTS Software Solutions, Columbia, Maryland, USA 3National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
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[email protected] Abstract—Modern multidimensional medical imaging efficiency of lossless compression for volumetric CT datasets technology produces very large amount of data especially from using five state-of-the-art video codecs, namely H264/AVC, the computed tomography modality. These volumetric dataset H265/HEVC, Lagarith, MSU, MLC, and compare them with opens new demands for big data storage and high-speed still-image codecs JPEG, JPEG2000, JPEG-LS as specified in communication systems which may be alleviated by image the DICOM standard [2]. compression techniques. Current image compression schemes adopted in the DICOM standard do not exploit the inter-slice II. METHODS correlation within three-dimensional (3D) dataset. Video compression may have a potential to improve the compression A. Data Description ratio by reducing the redundancy in volumetric medical images. Medical CT image datasets were obtained from 20 patients In this paper, we compare the performance of five lossless video underwent routine clinical examinations. All subjects gave codecs (H264, H265, Lagarith, MSU, MLC) and three still-image written consent form approved by the institutional review codecs (JPEG, JPEG2000, JPEG-LS) using 3D medical board of National Heart, Lung, and Blood Institute.