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.

唐氏综合症是影响人的生活的最常见的染色体疾病。唐氏综合症的早期发现对于更好地评估胎儿至关重要。可以通过从妊娠期的第一个（11-14周）和第二个中期（15-22周）记录的超声图像中识别各种参数来执行检测。最重要的特征是鼻骨短（发育不全）或鼻骨缺失，颈背厚度增加，胎儿心率（FHR），冠臀长度（CRL）和臂骨或大腿骨缩短。唐氏综合症的诊断使用侵入性和非侵入性筛选测试进行。有关唐氏综合症诊断的报道很多。本文回顾了各种成像方法的工作，