The considerations on effective lossless coding of non- smooth images are presented in this paper. Selection of the best not time consuming coding algorithms for a class of medical images is made a matter rather than completely new concept introduction. As a reference we consider the most efficient CALIC method, new lossless standard JPEG-LS and BTPC algorithm. Different methods of image scanning and 1D encoding are tested. Simple raster-scan data ordering followed by n-order arithmetic coding gives significant encoding efficiency for ultrasound images considered as a representative of the non-smooth image class. The lower bit rates could be achieved by additional statistical modeling in arithmetic coder based on the 12th order context quantized to one-order context. Therefore number of states in conditional probability model is reduced to overcome dilution problem. Finally, improved compression efficiency of non-smooth images in comparison to state-of-the-art CALIC algorithm is achieved. Average bit rate value is diminished over 30 percent. To compress smooth images the linear prediction scheme is incorporated for entire data redundancy reduction. The same model based on linear combination of adjacent pixels is used in prediction and entropy encoding steps. For smooth images our method performance is comparable to JPEG-LS and slightly worse than CALIC.