Liver Abscesses (LA) are pus-filled lesions. Amoebic Liver Abscesses (ALA), caused by protozoa called entamoeba histolytica and Pyogenic Liver Abscesses (PLA) produced by pus-forming bacteria are the two most common types encountered in clinical practice, most often in an emergency. LA debilitates the health and pushes the patients to bed. While pus culture-sensitivity tests confirm the cause of LA, contrast CT scans of the abdomen show the number of abscesses, their sizes, and the extensions. Telemedicine practice is on the rise to make healthcare ubiquitous. Image processing is becoming a part and parcel of teleradiology (a segment of telemedicine) to fill the gap between the number of radiologists versus the large patient pool who need early and accurate diagnoses and referrals. Clusterbased image segmentation is a useful step in grouping the image into the desired number of clusters. The k-Means Clustering (k-MC) technique is one popular method, used in this study on ALA and PLA contrast CT images. It observes that with the desired 2-clusters parameters such as normal liver tissue and pus-filled tissue, the algorithm gives better results in delineating PLA.