The increasing cesarean section (CS) rate is a global health issue, with a predicted exceedance of WHO guidelines by 2030. Accu rate labor assessment is effective in reducing the rate of CS, yet tra ditional methods like vaginal examination are subjective and uncom fortable. With the advent of ultrasound imaging technology, labor mon itoring can be facilitated through the measurement of two biometric parameters: the Angle of Progression (AoP) and the Head-Symphysis Distance (HSD). However, manual analysis of ultrasound images is time consuming and prone to error. The Intrapartum Ultrasound Grand Chal lenge (IUGC 2024) at MICCAI 2024 addresses this by promoting au tomated image analysis for labor monitoring. This involves classifying frames, segmenting structures, and measuring AoP and HSD. In this pa per, we presents the IUGC 2024 baseline methodology. Experiments were conducted on both the validation and test sets. The experimental results indicated that on the test set, an Acc of 0.518, a DSC of 0.801, a \(\varDelta AoP\) of 11.519 \(\circ \) , and a \(\varDelta HSD\) of 15.088 pixels were achieved.