Ultrasound exams have an important role in obstetrics due to its low cost, low risk and real-time capabilities. The advent of three-dimensional ultrasonography has made possible the use of the fetal volume as a biometric measurement to monitor its development. The quantification of the fetal volume requires a previous process of segmentation, which consists in the labelling of the pixels that belong to the object of interest in a digital image. There isn t, however, a standard methodology for fetal volumetry and most studies rely on manual segmentations. The segmentation of ultrasound images is particularly challenging due to the presence of artifacts as the speckle noise and acoustic shadows, and the fact that the contrast between regions of interest is commonly low. In this study, we have developed and tested a semiautomatic method of fetal segmentation in 3D ultrasound exams. Due to the aforementioned difficulties, good ultrasound segmentation methods need to make use of expected characteristics of the specific segmented structures. This thought has guided the development of our methodology that, through a sequence of simple steps, achieved good quantitative results in the segmentation task.