The arrival of high speed digital electronics and communication technologies to the radiological sciences is changing the method of acquiring, storing, viewing and communicating diagnostic images. Image modalities such as computed tomography, digital fluorography, ultrasound, nuclear medicine, and magnetic resonance imaging all depend on digital technologies. Even the conventional film/screen procedure is being considered for replacement by digital systems such as the laser stimulated luminescence plate and the electronic scanned selenium plate. As a result, a very large volume of digital diagnostic images will be generated. It is therefore essential to investigate techniques which can compress these images into a more compact form before storage and transmittal. Two years ago our department committed to the conversion of our operation from film-based to digital-based. To this end we have investigated and developed various aspects of the above technologies as they relate to digital-based operation. These include a centralized image processing laboratory, three communication systems which connect the laboratory to various diagnostic modalities, and multiple viewing stations. However, we still face a large volume of digital images that the current technologies are unprepared to cope with in a clinical environment. It is therefore essential to study image compression in order to reduce the communication and storage requirements for a digital-based radiology department. We have intensively studied radiological image compression during the past fifteen months and have developed techniques which produce excellent results. We can routinely encode any radiological image into a compressed data file with a compression ratio of better than 10:1; the reconstructed image from this compressed data does not show any visual degradation. However, in order for these image compression techniques to become clinically useful further investigation is necessary. Therefore, it is the goal of this research to: (1) further improve and develop the compression techniques, (2) generate a data base of selected radiological images for the evaluation of the compression techniques, (3) perform a rigorous visual perception study to compare the original image and the image reconstructed from compressed data, and (4) design and construct an electronic compression module based on the techniques developed so that the speed of compression is acceptable in a clinical environment.
Showing the most recent 10 out of 22 publications
