Automated Identification of Cephalometric Landmarks: Part 2- Might It Be Better Than human?

ObjectivesTo compare detection patterns of 80 cephalometric landmarks identified by an automated identification system (AI) based on a recently proposed deep-learning method, the You-Only-Look-Once version 3 (YOLOv3), with those identified by human examiners.Materials and MethodsThe YOLOv3 algorithm was implemented with custom modifications and trained on 1028 cephalograms. A total of 80 landmarks comprising two vertical reference points and 46 hard tissue and 32 soft tissue landmarks were identified. On the 283 test images, the same 80 landmarks were identified by AI and human examiners twice. Statistical analyses were conducted to detect whether any significant differences between AI and human examiners existed. Influence of image factors on those differences was also investigated.ResultsUpon repeated trials, AI always detected identical positions on each landmark, while the human intraexaminer variability of repeated manual detections demonstrated a detection error of 0.97 ± 1.03 mm. The mean detection error between AI and human was 1.46 ± 2.97 mm. The mean difference between human examiners was 1.50 ± 1.48 mm. In general, comparisons in the detection errors between AI and human examiners were less than 0.9 mm, which did not seem to be clinically significant.ConclusionsAI showed as accurate an identification of cephalometric landmarks as did human examiners. AI might be a viable option for repeatedly identifying multiple cephalometric landmarks.     

Resource utilization and costs of age-related macular degeneration

Data were analyzed from the 1999-2001 Medicare Beneficiary Encrypted Files for patients with age-related macular degeneration (AMD), an ophthalmic condition characterized by central vision loss. Classifying AMD subtype by International Classification of Diseases, Ninth Revision, Clinical Modifications (ICD-9-CM) (Centers for Disease Control and Prevention, 2003) code, resource utilization rates increased with disease progression. Individuals with more severe disease (wet only or wet and dry AMD) had greater costs than did those with less severe disease (drusen only or dry only). Costs among patients with wet disease increased yearly at rates exceeding inflation, possibly due in part to increased rates of treatment with photodynamic therapy among these individuals and the aging of the population.     

Update on anaesthesia and the immune response

Canadian Journal of Anesthesia/Journal canadien d'anesthésie - The available evidence supports the concept that anaesthetic agents influence a wide variety of specific and non-specific...     

Erythrocyte and plasma cholinesterase activity in normal pregnancy

Erythrocyte acetylcholinesterase and plasma cholinesterase was estimated in 50 normal pregnant women and 22 age matched normal non-pregnant women. Plasma cholinesterase was significantly decreased while erythrocyte cholinesterase was significantly increased during pregnancy. These changes may be related to altered haemodynamics and or other inter-related changes occurring in pregnancy.