High compression of nuclear medicine dynamic studies

Abstract

As data compression plays now an important role in the development of medical PACS, a technique has been developed for medical image sequences storage and transmission in order to obtain very high compression ratio: in dynamic nuclear medicine studies it can achieve a compression ratio as high as 100:1 without significant degradation. The implemented technique combines two methods which multiply their effects. In a first step, a principal component analysis (PCA) of the image series is performed. It extracts a limited number of principal components and their associated images. For data compression it is not necessary to perform an oblique factor analysis to estimate the so-called 'physiological functions' and their spatial distributions as in factor analysis of dynamic structures (FADS). In a second step, the principal images are compressed by means of a transform coding procedure: an adaptive block-quantization technique using the 2D discrete cosine transform (DCT) is implemented, followed by a statistical quantization method to encode the DCT coefficients. To reconstruct the principal images, an inverse DCT is applied. Then the original series is computed from the reconstructed images combined with the principal components which have been stored without any modification. The reconstructed series is compared to the original series, as well as the time activity curves generated on different regions of interest (ROI) and the factor estimates obtained using FADS performed on the two series. Method and evaluation are illustrated on an example of first pass radionuclide angiocardiography.

Comparison of the Usefulness of the MTT, ATP, and Calcein Assays to Predict the Potency of Cytotoxic Agents in Various Human Cancer Cell Lines

“…[13][14][15]18 It has also been used to define similar and deviating responses among biological data (variables). [19][20][21][22][23] Results of the multiple intercorrelation analysis of the data in Table 1 are displayed in Table 2A (correlation matrix) and Table 2B (factor loadings of the 7 variables). The correlation matrix gives a 1st overview on strong and weak correlations between the 7 variables and shows-with 2 exceptions-correlation coefficients of > 0.824 (Table 2A) one major advantage of the PCA results (factor loadings, Table 2B) is the enormous data compression reducing the complexity of the correlation matrix.…”

“…PCA and factor analysis has been used as a statistical method not only to reduce the number of dimensions in data analysis and investigate multiple intercorrelations between variables but also to define similar or deviating responses among biological variables. [13][14][15][18][19][20][21][22][23] Ninety-three percent of the total variance of the 7 variables in Table 1 could be explained by 1 PC showing that the results and responses of the cell lines are identical. A criterion to choose the number of PCs is the Kaiser criterion and the scree plot (Fig.…”

Definition of Compression Ratio: Difference Between Two Commercial JPEG2000 Program Libraries

“…Some researchers [3][4][5][6][7]12,13,25,26,[29][30][31][32] referred to the size of the total uncompressed image file (including the padding bits) as the size of the original image data in the definition of compression ratio, and other researchers 27,28,33 referred to the significant data size (without the padding bits). Furthermore, the definition of the compression ratio is missing in many studies 2,[8][9][10][11][14][15][16][17][18][19][20][21][22][23][24] including those using library A.…”

“…[3][4][5][6][7]12,13,[25][26][27][28][29][30][31][32][33] Furthermore, the definition is different between commercial compression libraries that are used in commercial Picture Archiving and Communication Systems (PACS). Because the compression ratio is indispensable and the most practical measure in determining and communicating the acceptable compression level, it is important to keep the definition consistent between radiologists, researchers, and vendors.…”

Temporal and Spatial Compression of Dynamic Positron Emission Tomography in Sinogram Domain

“…18 Some investigators have previously applied PCA and DCT such as JPEG in the image domain as the data compression technique for dynamic medical imaging. 19,20 However, JPEG can create blocking artifacts at high compression ratios, which can affect the reconstruction. In this paper we will systematically analyze the performance of the new compression methods based on PCA with JPEG2000 in the sinogram domain (S-PCA + S-JPEG2000) using the Zubal phantom simulated data 21 and four clinical patients studies.…”