Integration of eigentemplate and structure matching for automatic facial feature detection

An algorithm is proposed for facial feature detection from a facial image. The algorithm consists of the bottom-up and the top-down interpretation processes, which work with the feature matching module and the structure matching module. Experimental results show that the proposed algorithm can detect no less than five features in 99.3% of the frontal views and can work even if the face orientation is unknown</p

Bone Regeneration in Artificial Jaw Cleft by Use of Carbonated Hydroxyapatite Particles and Mesenchymal Stem Cells Derived from Iliac Bone

Objectives of the Study. Cleft lip and palate (CLP) is a prevalent congenital anomaly in the orofacial region. Autogenous iliac bone grafting has been frequently employed for the closure of bone defects at the jaw cleft site. Since the related surgical procedures are quite invasive for patients, it is of great importance to develop a new less invasive technique. The aim of this study was to examine bone regeneration with mesenchyme stem cells (MSCs) for the treatment of bone defect in artificially created jaw cleft in dogs. Materials and Methods. A bone defect was prepared bilaterally in the upper incisor regions of beagle dogs. MSCs derived from iliac bone marrow were cultured and transplanted with carbonated hydroxyapatite (CAP) particles into the bone defect area. The bone regeneration was evaluated by standardized occlusal X-ray examination and histological observation. Results. Six months after the transplantation, perfect closure of the jaw cleft was achieved on the experimental side. The X-ray and histological examination revealed that the regenerated bone on the experimental side was almost equivalent to the original bone adjoining the jaw cleft. Conclusion. It was suggested that the application of MSCs with CAP particles can become a new treatment modality for bone regeneration for CLP patients

Scale space calibrates present and subsequent spatial learning in Barnes maze in mice

Animals are capable of representing different scale spaces from smaller to larger ones. However, most laboratory animals live their life in a narrow range of scale spaces like home-cages and experimental setups, making it hard to extrapolate the spatial representation and learning process in large scale spaces from those in conventional scale spaces. Here, we developed a 3-meter diameter Barnes maze (BM3), then explored whether spatial learning in the Barnes maze (BM) is calibrated by scale spaces. Spatial learning in the BM3 was successfully established with a lower learning rate than that in a conventional 1-meter diameter Barnes maze (BM1). Specifically, analysis of exploration strategies revealed that the mice in the BM3 persistently searched certain places throughout the learning, while such places were rapidly decreased in the BM1. These results suggest dedicated exploration strategies requiring more trial-and-errors and computational resources in the BM3 than in the BM1, leading to a divergence of spatial learning between the BM1 and the BM3. We then explored whether prior learning in one BM scale calibrates subsequent spatial learning in another BM scale, and found asymmetric facilitation such that the prior learning in the BM3 facilitated the subsequent BM1 learning, but notvice versa. Thus, scale space calibrates both the present and subsequent BM learning. This is the first study to demonstrate scale-dependent spatial learning in BM in mice. The couple of the BM1 and the BM3 would be a suitable system to seek how animals represent different scale spaces with underlying neural implementation. Significance Statement Animals are capable of representing different scale spaces. However, whether scale space calibrates goal-directed spatial learning remains unclear. The Barnes maze is a well-established experimental paradigm to evaluate spatial learning in rodents. Here, we developed a larger scale 3-meter diameter Barnes maze (BM3) then compared various navigation features in mice between the BM3 and a conventional 1-meter diameter Barnes maze (BM1). We demonstrated that spatial learning on the BM3 was established, but required more trial-and-error and computational resources than in the BM1, prompting mice to visit certain places persistently. Such learning experiences in the BM3 facilitated subsequent spatial learning in the BM1, but not vice versa. These results suggest that scale space calibrates present and subsequent spatial learning

A Ruptured Distal Posterior Inferior Cerebellar Aneurysm Our Case and Review of the Literature

We present a case of ruptured distal posterior inferior cerebellar artery (PICA) aneurysm, and review the literature and discuss the treatment strategy. A 77-year-old woman presented with the sudden onset of severe headache, nausea and vomiting. Computed tomography revealed an intraventricular hemorrhage, predominantly in the fourth ventricle and hydrocephalus with a thin subarachinoid hemorrhage (SAH). Angiography revealed an aneurysm arising at the turning point of the vessel, from the telovelotonsillar segment of the right PICA. On the 17 day after the onset, repeated angiography revealed a smaller aneurysm than the one detected on the first day at the same place and with no spasm. On the 22 day, the aneurysm was proved to be partially thrombosed and was safely clipped via a right lateral suboccipital approach. SAH with a fourth ventricular hemorrhage or an isolated fourth ventricle hemorrhage should raise the suspicion of a distal PICA aneurysm. Aneurysms of the distal PICA have often been reported to arise at a turning point of the artery rather than at a junction of the vessel. It is suggested that the pathogenesis could be hemodynamic stress that has developed due to embryological factors. Distal PICA aneurysms have often gone detected in many previous cases because of thrombosis inside the aneurysms. Thus, particularly in the case of intentionally delayed surgery, we recommend repeated angiography under various conditions to identify how the aneurysm develops just before surgery

Integration of eigentemplate and structure matching for automatic facial feature detection

An algorithm is proposed for facial feature detection from a facial image. The algorithm consists of the bottom-up and the top-down interpretation processes, which work with the feature matching module and the structure matching module. Experimental results show that the proposed algorithm can detect no less than five features in 99.3% of the frontal views and can work even if the face orientation is unknown</p