Down syndrome is the most common chromosomal disorder that affects the life of a person. Early detection of Down syndrome is important and significant for a better assessment of the fetus. The detection can be performed by identifying various parameters from the ultrasound images recorded during the 1st (11-14 weeks) and 2nd trimester (15-22 weeks) of the gestational period. The most important features are short Nasal bone (Hypoplasia) or absence of nasal bone, increased thickness of the back of the neck, fetal heart rate (FHR), crown-rump length (CRL) and shortening of arm bone or thigh-bone. The Diagnosis of Down syndrome is performed using invasive and noninvasive screening tests. There are many reported studies on the diagnosis of Down syndrome. This paper reviews the work on various imaging methods, and a technique reported for the detection of Down syndrome and introduces the use of Deep Learning techniques in identifying the presence of Down syndrome.