Telepathology is a means of practising pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial.  This is because conventional image compression algorithms achieve data compression without knowledge of the diagnostic content.  Often images are lossily compressed at the expense of corrupting informative content.  None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded.  Their sole objective is to compress and transmit the images as fast as possible.  By contrast, this paper presents a novel image compression technique which exploits knowledge of the slide diagnostic content.  This 'content based' approach combines lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression.  Standard compression algorithms can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.  This 'content based' approach will improve the performance of the pathologists as well as the patient's prognosis.