This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for the human eye to discern because of low contrast, are generally very well preserved by these compression algorithms. By applying a wavelet decomposition to the whole image and to specific regions of interest (ROI), and by understanding how the lossy quantization step attenuates signals in those decomposition energy subbands, much can be learned about how tolerant various anatomical structures are to compression. High-frequency anatomical structures that have their energy represented by a few large coefficients (in the wavelet domain) will be well preserved, while, those structures with high frequency energy distributed over numerous smaller coefficients are the most vulnerable to compression. Digitized films showing subtle chest nodules, a subtle stress fracture, and CT and MR images are used to show these results.