Jean Lienard

Real‐time distortionless high‐factor compression scheme

Nowadays, digital subtraction angiography systems must be able to sustain real-time acquisition (30 frames per second) of 512 x 512 x 8 bit images and store several sequences of such images on low cost and general-purpose mass memories. Concretely, that means a 7.8 Mbytes per second rate and about 780 Mbytes disk space to hold a 100-s cardiac examination. To fulfill these requirements at competitive cost, a distortionless compressor/decompressor system can be designed: during acquisition, the real-time compressor transforms the input images into a lower quantity of coded information through a predictive coder and a variable-length Huffman code. The process is fully reversible because during review, the real-time decompressor exactly recovers the acquired images from the stored compressed data. Test results on many raw images demonstrate that real-time compression is feasible and takes place with absolutely no loss of information. The designed system indifferently works on 512 or 1024 formats, and 256 or 1024 gray levels.

The 6σ quality approach for quantitative arteriography performance improvement

Quantitative angiography is a medical application where the user requires tools whose operational results in term of accuracy, precision, robustness and reliability must be extensively assessed and validated for clinical use. In this study, the 6σ methodology has been applied to analyze the performances of the General Electric QA software method. In particular, the catheter calibration procedure was identified as the weakest function in term of sensitivity to procedure parameters, like point-spread-function, field-of-view, catheter dimensions. It was therefore improved by following a design for 6σ scheme, and the main parameters that govern the QA accuracy and precision were put under quantifiable control.

Reliability of myocardial perfusion quantification in angiography using a digital flat panel cardiac system

Discordance between lesion severity from angiocardiography and physiological effects has been reported elsewhere. Quantification of myocardial perfusion during the angiography procedure may supply additional information about short- and long-term outcomes and may be helpful for clinical decision making. In previous works, myocardial perfusion has been assessed using time density curves (TDC), which represent the contrast medium dilution over time in the myocardium. The mean transit time (MTT), derived from the TDC, has been reported as a good indicator of the regional myocardial perfusion. Our objective is to estimate the accuracy and reproducibility of MTT estimation on digital flat panel (DFP) images. We have simulated typical myocardium TDC obtained with a DFP cardiac system (Innova 2000, GE), taking into account scatter and noise. Logarithmic or linear subtractions have been applied to derive a contrast medium concentration proportional quantity from image intensity. A non-linear minimisation realises the model curve fitting. MTT estimates are more stable with linear subtraction in presence of scatter. However logarithmic subtraction presents smaller bias when scatter level is small. Both approaches are equally sensible to image noise. Linear subtraction should be preferred. Image noise has a high influence on MTT accuracy and we may reduce.