Image compression is a serious problem in the medical field for the storage and transmission of medical data. When medical images are transmitted, it consumes transmission bandwidth, storage capacity, and power consumption due to its large amount of information, and hence a hybrid block-based technique with Hadamard transform and Huffman encoder compression technique is proposed for transmitting medical data via networks. Initially, the integer wavelet transform (IWT) decodes the input image, and transformation is performed in LL sub-bands by lossless Hadamard transform (LHT) and DC prediction (DCP) to discard the correlation inside and in adjacent blocks, respectively. Encoding can be done with or without transformation by LHT. Finally, to compress the resultant coefficients, IWT-LHT-Huffman encoder/IWT-LHT-Arithmetic encoder is used. Experimental result reveals the comparison of IWT-LHT-Huffman, IWT-LHT-Arithmetic compression, and JPEG lossless compression models. From the obtained results, the IWT-LHT-Arithmetic compression algorithm generates superior results with less computational complexity when compared with the IWT-LHT-Huffman and JPEG lossless compression schemes.