Medical imaging has improved considerably and contributed to the creation of remarkable achievements in disease treatment over the past decades. Nowadays it is completely general to use medical imaging in everyday medical practice to support non-invasive or semi-invasive medical interventions. Thanks to the technical progress of computers, digitization of imaging brought in a new era in the field of medical imaging. The stored digitized data and improved technology allow creating more accurate and precise treatments. At the same time, the larger world population causes an increased demand for medical treatment, which stimulates the era of automatization in medical imaging. In recent years the number of the technology-driven developments are increasing for better treatments becoming stoppable in the age of small and mobile computers. Despite of the clear progress, medical image processing is a non-trivial task, and is one of the most widely researched fields. Due to the increasing size and diversity of data obtained by better and better sensors, the most important challenges in this field are the complexity of the image processing problem and the computation time of its algorithmic solutions. To reduce complexity and raise the accuracy of the solutions, splitting the problem into subtasks is a known answer. The detection of the location of an object on an image is one of the most common tasks in the field of medical image processing. In this task a classification procedure of the image pixels is solved by the help of classifiers. The reason for composing ensembles from individual classifiers is to make joint classification from the aggregated data instead of using only one classifier. These ensembles are popular to use since they can raise the accuracy of the final answer and make it possible to apply existing research results. For decision making, majority voting is a usually applied model. Although the ensembles can reduce the complexity in the level of sub-tasks, the complete ensemble-based software solution mostly has great computational demand.