Pregnancy requires constant monitoring by health care providers to avoid conditions that may threaten the lives of the fetus and the mother at birth. For labor management, the diagnosis of fetal presentation is essential to guarantee delivery viability. A direct indicator of fetal presentation is the fetal head location, which can be placed close to the canal birth (cephalic, head-first) or far from the canal birth (breech, feet first). Unlike urban areas, the population in rural zones experience difficulties in accessing healthcare monitoring. Although telemedicine has helped bring medical technology closer to these regions, the diagnosis still requires medical specialists. This study presents an automatic three-stage detection framework for assessing the fetal head position (and hence the fetal presentation). The first stage involves applying morphological filtering, intensity-based thresholding, and shapebased filtering for a preliminary head detection and segmentation. The second stage comprises segmentation enhancement using a combinatory approach. The third stage uses the detection results to depict the spatial location likelihood of the head, which indicates the head location and fetal presentation. Fifteen volunteers in the third trimester of pregnancy were evaluated, and the fetal presentation was diagnosed. These results were compared with the diagnosis of a radiologist (used as a gold standard). The proposed method presented a 100% accuracy in determining the fetal presentation, albeit a limited number of cases evaluated.