Dunling Li

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Modern multidimensional medical imaging technology produces very large amount of data especially from the computed tomography modality. These volumetric dataset opens new demands for big data storage and high-speed communication systems which may be alleviated by image compression techniques. Current image compression schemes adopted in the DICOM standard(More)
The demand for efficient data transmission and storage have increased substantially in recent years with the rise of data size and complexity. Video content accounted for 64% of all-world-internet-traffic in 2014, and will reach 80% by 2019. The volume of video content is increasing drastically with the advances in device and communication technology, as(More)
The diagnostic value of a medical image after it has been decompressed is a very practical measure of the image quality and the compression method. A computational observer can be used to make decisions based on an image and thus can provide an assessment of diagnostic value. This paper provides a closed-form estimate of the channelized Hotelling observer's(More)
We report a method for evaluating the performance of model observers for decompressed images in analytical form using compression noise statistics. It derives test statistics and detectabilities for the ideal observer, the nonprewhitening observer, the Hotelling observer, and the channelized Hotelling observer (CHO) on decompressed images. The derived CHO(More)
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