In this article, we present experiments aimed to identify a suitable compression algorithm for colour retina images (Schaefer & Starosolski, 2006). Such an algorithm, in order to prove useful in a real-life PACS, should not only reduce the file size of the images significantly but also has to be fast enough, both for compression and decompression. Furthermore, it should be covered by international standards such as ISO standards and, in particular for medical imaging, the Digital Imaging and Communication in Medicine (DICOM) standard (Mildenberger, Eichelberg, & Martin, 2002; National Electrical Manufacturers Association, 2004). For our study, we therefore selected those compression algorithms that are supported in DICOM, namely TIFF PackBits (Adobe Systems Inc., 1995), Lossless JPEG (Langdon, Gulati, & Seiler, 1992), JPEG-LS (ISO/IEC, 1999), and JPEG2000 (ISO/IEC, 2002). For comparison, we also included CALIC (Wu, 1997), which is often employed for benchmarking compression algorithms. All algorithms were evaluated in terms of compression ratio which describes the reduction of file size and speed. For speed, we consider both the time it takes to encode an image (compression speed) and to decode (decompression speed), as both are relevant within a PACS.
Key Terms in this Chapter
Image compression: Reduction of the amount of memory used to store an image.
Diabetic retinopathy: A common complication of diabetes leading to progressive damage of the eye’s retina.
DICOM: A medical imaging standard describing how image information can be exchanged.
Screening: Checking for a disease in people without symptoms.
Ophthalmology: The science of eye medicine.
Lossless Compression: Compression from which the original information can be recovered without loss.
Retina: A thin layer of neural cells which lines the inner eyeball.