Title :
Lossless Compression of Segmented CT Medical Images According to the Hounsfield Scale
Author :
Spelic, D. ; Mongus, Domen ; Zalik, Borut
Author_Institution :
Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor, Slovenia
Abstract :
In this paper, a method for loss less compression of medical CT images is presented. The method allows separate compression, transmission, and decompression using data segmentation based on the Hounsfield scale. The presented method modifies our previous method by modifying the prediction scheme. The prediction scheme omits the inter-slice prediction to allow random access into the compressed segmented CT slides. The results show that the obtained compression rate is comparable to previous method.
Keywords :
computerised tomography; data compression; image coding; image segmentation; medical image processing; CT medical image segmentation; Hounsfield scale; data segmentation; interslice prediction; lossless compression; Computed tomography; Data visualization; Image coding; Image segmentation; Medical diagnostic imaging; Predictive models; Hounsfield scale; image compression; segmentation;
Conference_Titel :
Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on
Conference_Location :
Noosa, QLD
Print_ISBN :
978-1-4577-2006-2
DOI :
10.1109/DICTA.2011.56
