Recognition of fetal facial expressions for neurobehavioral assessment using Relaxing-Mismatch Global Sequence Time Warp Kernel
Conference proceedings article
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
ไม่พบข้อมูลที่เกี่ยวข้อง
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Kanitthakun S., Chamnongthai K.
ผู้เผยแพร่: Hindawi
ปีที่เผยแพร่ (ค.ศ.): 2012
หน้าแรก: 54
หน้าสุดท้าย: 57
จำนวนหน้า: 4
ISBN: 9781467350815
นอก: 0146-9428
eISSN: 1745-4557
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
Most pregnant women are positive feeling and happy when the ultrasound scanning results the normal detection. However, if the finding gives unexpected anomaly detection, it is the cause of unnecessary anxiety and worry. Fetal neurobehavioral assessment is one of the antenatal assessments. The goal is to identify fetal being that is well or at risk and expected that the risk can be prevented or reduced. Fetal behavioral variables, movements and postures, are an indicator of significantly spontaneous activity of fetal central nervous system. Fetal behavioral studies suggest that the frequency of some facial fetal expressions at risk differs from normal. For instance, hydrocephalic fetus has less a fewer eye movement than normal fetuses. Although the individual ultrasound scan has been successively used, the knowledge, the reliability, and the objective are required with the clinical professional experience. The limitation and the human fatigue are often caused of biasing and failing the significant consideration of available information. Thus, automatic facilitated fetal facial expression assessment becomes necessary. Although, Automatic facial expression recognition is widely used in human facial expressions, the system suffers with the time axis distortion. In medical diagnosis, precise recognition system is required. The Relaxing-Mismatch Global Sequence Time Warp Kernel is proposed for natural fetal facial expression recognition. ฉ 2012 IEEE.
คำสำคัญ
3D/4D ultrasound, facial expression recognitiont, fetal neurobehavioral assessment, Kernel
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