X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
2001-07-13
2002-10-22
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S901000
Reexamination Certificate
active
06470065
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates generally to the art of medical diagnostic imaging and in particular to a method and apparatus for a computer tomography of the type wherein the measurement data are compressed en route to the computer that reconstructs images of the scanned object.
2. Description of the Related Art
In computer tomography, raw data is acquired during a scan of an object irradiated by X-rays from an X-ray source from different directions (projections) and the X-rays attenuated by the object are incident on a number of sensors (channels) that are arranged in four rows of a radiation detector. The X-ray source and the detector are mounted on rotor or gantry. Accordingly, for every rotor position, four vectors of data, (“fan” or “reading”) are obtained. During a scan, the rotor is rotated in angular steps, each step giving a new reading. The set of readings for one full turn of the rotor is referred to as “rotation”. Either after or during a full rotation, the target is moved in a direction orthogonal to the rotors plane and data accumulated over many rotations are combined into one file that is being preceded by a file header and an additional header for each vector.
In computer tomograph scans having 672 sensors with 4 rows there are 672*4 channels and 2320 readings per rotation. Accordingly, 6236160 measurements per rotation are obtained with each measured value stored as an unsigned word of 16 bit. Thus, there are roughly 12 MByte of data per rotation. The number of rotations depends on the size of the target to be scanned, (for example approximately 10 to 20 rotations are required for scanning a human head). As such, a substantially high array of data is being generated that in turn should be transmitted to a central processing unit for a reconstruction of the scanned object's images.
Therefore, compression methods capable of efficiently compressing these data en route to the computer will improve on the overall operation of CT imaging devices by reducing the storage space and bandwidth required for transmission of the data to the central processing unit.
Generally, in any data compression method for textual data, one deals with a stream of symbols drawn from a known alphabet and attempts to encode the symbols in a manner that storing the encoded symbols take the least possible space. An obvious way to achieve this goal is to assign short codes to symbols that appear frequently in the stream and longer codes to less frequent symbols. For example, Huffman coding is a popular and simple way to implement this strategy.
In codings, the entropy rate of a source is a number that depends only on the statistical nature of the source. In particular, in a First-Order Model where the characters are statistically independent of another the entropy is h=&Sgr;n
i
log
2
(p
i
), with n
i
the number of occurrences of symbol i in the data stream and p
i
its probability. Based on information theory, the entropy is a lower bound for the number of bits needed to encode a message or a stream of data. However, these probabilities p
i
are usually not constant throughout the stream and depend on the context. For example, when compressing German or English texts, the probability for a “u” is very high after a “q”. A lot of effort in compression research has been spent on modeling the context, so that a high compression rate can be achieved by context-dependent coding.
One method utilized for data compression is a local prediction based compression. As illustrated by the entropy formula above, the size of the encoded data can be reduced by increasing the probabilities of symbols; (for example, by decreasing their numerical range). Accordingly, by storing differences between data values, one expects to reduce the numerical range of values and to increase the probability of values in the neighborhood of zero. These differences are calculated based on a predicted value. As the input stream is processed, for each data point, a predicted value is calculated based on a data already seen. The difference between this prediction and the actual value is then sent to an entropy encoder.
U.S. Pat. No. 5,592,523 discloses a data compression unit between a rotating gantry and a stationary gantry of a CT scan device. This patent does not disclose a noise reduction technique in conjunction with the compression of data. Furthermore, this patent does not disclose an algorithm for data compression that takes in to account the certain periodicity superimposed to the acquired data in a matrix format. This periodicity occurs because the data is acquired by using four arrays of sensors in one reading.
SUMMARY OF THE INVENTION
It is an object of the present invention to provide a system for compressing data acquired by means of an X-ray source, before the data is being transmitted to a central processing unit. The above object is achieved by utilizing an entropy coding method for data compression in a data compression unit of a computer tomography device.
In one embodiment, the data compression unit is connected to the stationary module of the medical imaging device. The raw data acquired by means of an X-ray source is being stored as a data set in a matrix format with i rows and j columns, i, j being positive integers. A compression algorithm is then performed upon this data matrix by the compression unit. This results in data being compressed before it is sent to the computer. Once received by the computer, a reconstruction of the object scanned is performed based on the compressed data. The reconstructed image is then displayed on a monitor.
In another embodiment, a certain periodicity is being superimposed to the matrix of data. Taking this periodicity into account leads to significant compression improvements. The invention further allows for fast operation (0.2 ms/projection). Furthermore, a simple code hardware implementation is possible. In addition, only four projections have to be kept in memory during compression/decompression with no need to transfer auxiliary tables from the compressor to a decompressor.
REFERENCES:
patent: 5592523 (1997-01-01), Tuy et al.
patent: 5825830 (1998-10-01), Kopf
“A Method for the Construction of Minimum-Redundancy Codes,” Huffman, Proceedings of the I.R.E., Sep., 1952, pp. 1098-1101.
“Arithmetic Coding for Data Compression,” Witten et al., Communications of the ACM, vol. 30, No. 6, Jun., 1987, pp. 520-540.
“LOCO-I: A Low Complexity, Context-Based. Lossless Image Compression Algorithm,” Weinberger et al., Proceedings of the IEEE Data Compression Conference, Mar.-Apr., 1996.
“Data Compression with the Burrows-Wheeler Transform,” Nelson, Sep., 1996.
“Practical Huffman Coding,” Schindler, Compression Consulting, Aug.-Oct., 1998.
Bruce David V.
Schiff & Hardin & Waite
Siemens Aktiengesellschaft
LandOfFree
Apparatus for computer tomography scanning with compression... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Apparatus for computer tomography scanning with compression..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Apparatus for computer tomography scanning with compression... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2922572