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Biomedical subjects

Shen-Chuan Tai

Publications and source records attributed to Shen-Chuan Tai.

3 recordsLinked to original sources

Enhancing ultrasound images by morphology filter and eliminating ringing effect.

Various medical image compression techniques have been proposed for accelerating image propagation in many applications. JPEG2000 is a new generation technique that can encode near lossless ultrasound images at medium bit-rate with diagnostically acceptable quality. Because the coder of JPEG2000 is based on wavelet transform, the reconstructed image will contain some ringing artifacts. Some de-ringing algorithm must be applied to enhance image quality. This study presents quad-tree decomposition and a set of morphological filters for reducing the ringing artifacts of ultrasound images. Specifically, the presented morphological filters use eight predefined morphological operations, including four structuring elements (SE) that include both dilation and erosion. The proposed voting strategy can be used to select the morphological filter for each block to optimize decoded image quality. Image quality can be enhanced by applying the appropriate morphological filter to each block. Experimental results demonstrate that the proposed technique enhances reconstructed ultrasound image quality compared to JPEG2000 at the same bit-rate in terms of both PSNR and the perceptual results.

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A 2-D ECG compression method based on wavelet transform and modified SPIHT.

A two-dimensional (2-D) wavelet-based electrocardiogram (ECG) data compression method is presented which employs a modified set partitioning in hierarchical trees (SPIHT) algorithm. This modified SPIHT algorithm utilizes further the redundancy among medium- and high-frequency subbands of the wavelet coefficients and the proposed 2-D approach utilizes the fact that ECG signals generally show redundancy between adjacent beats and between adjacent samples. An ECG signal is cut and aligned to form a 2-D data array, and then 2-D wavelet transform and the modified SPIHT can be applied. Records selected from the MIT-BIH arrhythmia database are tested. The experimental results show that the proposed method achieves high compression ratio with relatively low distortion and is effective for various kinds of ECG morphologies.

Algorithms↗

Beat-based ECG compression using gain-shape vector quantization.

An electrocardiogram (ECG) data compression scheme is presented using the gain-shape vector quantization. The proposed approach utilizes the fact that ECG signals generally show redundancy among adjacent heartbeats and adjacent samples. An ECG signal is QRS detected and segmented according to the detected fiducial points. The segmented heartbeats are vector quantized, and the residual signals are calculated and encoded using the AREA algorithm. The experimental results show that with the proposed method both visual quality and the objective quality are excellent even in low bit rates. An average PRD of 5.97% at 127 b/s is obtained for the entire 48 records in the MIT-BIH database. The proposed method also outperforms others for the same test dataset.

Algorithms↗