jump to download contact author acknowledgments
The set was prepared to evaluate the performance of lossless image compression algorithms for medical and natural continuous tone grayscale images. The set contains natural continuous tone grayscale images of various bit depths (up to 16 bits), various sizes (up to about 4 millions of pixels) and medical images of various modalities (CR, CT, MR, and US). In the set, image groups were defined, to permit performance analysis based on average results for the whole group, rather than on results for single images. The biggest group, called normal, is for evaluating algorithmsí performance in a typical case, i.e., average results of compressing images from the normal group may serve as a measure of algorithmsí average performance for continuous tone gray-scale images. A collection of smaller groups permits to analyze or compare results with respect to imagesí bit depths, sizes, or medical image modality. The set contains also non-typical images, which do not belong to the normal group. To analyze the algorithmsí performance on noisy data special images with added noise were prepared. To estimate the best-case and the worst-case performance of algorithms, easily compressible and incompressible pseudo-images were also generated.
More detailed description of the groups and of the individual images is avaliable here (pdf).
The compression ratios and compression speeds obtained by several algorithms for the set are reported in: Starosolski, R.: Performance evaluation of lossless medical and natural continuous tone image compression algorithms. Proc. SPIE, 2005, Vol. 5959, pp. 116-27, (©).
Other results obtained for the set may be found here and here.
Download the set
The set is publicly available, it may be downloaded from this page (http://sun.aei.polsl.pl/~rstaros/mednat/index.html). All the images are stored in the PGM P5 format (grayscale, binary, Big Endian). The set is split into three parts containing natural, medical, and other (non-typical) images respectively, each part is contained in single .zip archive.
natural images (68MB) downloadContact the author
medical images (54MB) download
other images (8MB) download
The set was prepared as a part of the research project Nr 4 T11C 032 24, which was fully supported by the Grant of the Polish National Research Committee (KBN). Above Grant was carried out at the Institute of Computer Science, Silesian University of Technology, in years 2003 and 2004. The author would like to thank people and institutions, which in helped in obtaining test images and kindly agreed to include the images in the set. Natural images are scanned photographs by Dr Jacek Szedel (Silesian University of Technology). Some of the medical images were supplied by Prof. Ewa PiÍtka (Silesian University of Technology), some others are Philips DICOM Reference Medical Images of Philips Medical Systems (ftp://ftp-wjq.philips.com/medical/interoperability/out/Medical_Images/). All the remaining medical images are the publicly available DICOM images, donated by various medical equipment vendors to the RSNA conference (ftp://wuerlim.wustl.edu/pub/dicom/images/version3/).