The study aimed to explore the application value of MRI images based on the optimized self-adaptive edge detection algorithm in the diagnosis of placenta previa and in the prediction of postpartum hemorrhage. Specifically, a self-adaptive edge detection algorithm was constructed based on optimized edge operators, with the nearest scale parameters analyzed. It was then used to process the MRI images of 36 patients with placenta previa. MRI images of different types of placenta previa were analyzed. The results found that the placenta of the complete placenta previa was attached to the lower wall of the uterus and covered the internal cervix in U shape, and the placenta adhered to the anterior and lower wall of the uterus, with widespread placenta accreta noted. With the results of cesarean section as the standard, it was observed that 2 cases of complete placenta previa were diagnosed as partial placenta previa. The diagnostic accuracy rate was 94.44%, which was not notably different from the results of cesarean section
p
>
0.05
. The postpartum hemorrhage rate and hysterectomy rate of complete placenta previa were higher than partial placenta previa and marginal placenta previa, and the difference was notable
p
<
0.05
, but no notable differences were noted in placenta adhesion, placenta accreta, neonatal death, and neonatal asphyxia between the three types of placenta previa
p
>
0.05
. The incidence of thinned myometrium, placenta penetrating the cervix, placenta accreta, and uneven placental signal in patients with postpartum hemorrhage was higher versus those without postpartum hemorrhage, and the difference was notable
p
<
0.05
. In a word, MRI images based on the self-adaptive edge detection algorithm can clearly show the status of placenta previa and exhibit better diagnosis effects and a higher accuracy rate. The thinned myometrium, the placenta penetrating the cervix, placenta accreta, and uneven placental signal may be the related risk factors for postpartum hemorrhage in patients with placenta previa.