Search

SUMMARY: The sectional anatomy of a cat head is essential when interpreting CTs and MRIs of the region. In learning the sectional anatomy, sectioned images of a cat could be quite effective data. The main objective was to assist veterinary physicians who learn the sectional anatomy of a cat head by presenting high-quality sectioned images. A short-haired female cat was frozen and sectioned frontally using a cryomacrotome. Every sectioned surface in real body color was photographed with a digital camera. The frontal planes were stacked to produce dorsal and sagittal planes. High-quality sectioned images of a cat head allowed the identification of small, complicated structures. The notable structures were as follows: each bone of the cranium, structures of the brain, tympanic cavity (larger than human), oval window (larger than human), vestibular nerve, cochlear nerve, ear ossicles, six extraocular muscles, pupil (larger than human), retractor bulbi muscle (not found in human), optic nerve, olfactory bulb (considerably large), vomeronasal organ duct (not found in human), infraorbital gland (not found in human), masticatory muscles (larger than human), maxillary nerve (larger than human), and mandibular nerve. This pacesetting report describes the detailed head structures of a cat from the viewpoint of sectional anatomy. The sectioned images will be given to other interested researchers free of charge.

SUMMARY: The purpose of this research was to enable anyone to learn the sectional anatomy of the head anywhere, anytime by presenting software to browse sectioned images on a Google Android mobile device. Among the 2,343 sectioned images at 0.1 mm intervals, 234 sectioned images at 1 mm intervals were chosen. The corresponding 234 segmented images containing 236 head structures were selected. The software of the mobile version was programmed and debugged in the Java programming language. The folders of the sectioned images and segmented images and the txt file of the segmentation data were arranged in the source code of the software. The software was distributed free of charge at the homepage (neuroanatomy.kr) and Google Play Store. After installing the software, the sectioned images and corresponding segmented images could be browsed by touching and swiping the screen. In the medical category of the Google Play Store, the software earned a good reputation. The software of the Android mobile version was usable regardless of the time and place. The software is under the authors’ non-commercial policy. Other investigators may modify the mobile software to browse their own images. The mobile version of the software will aid medical students and doctors in learning sectional anatomy.

Objectives: Authors intended to confirm whether simultaneous watching of the surface and the volume models contributes to foot anatomy.Methods: Outlines of the skin and foot muscles were traced in the sectioned images of a cadaver to build surface models of the structures. After the outlines were filled with appointed colors, the sectioned images, including the colors, were stacked to yield the volume model of foot which was stripped from the skin little by little.Results: The stripped volumes illustrated the depth of the individual foot muscles. In clinics, the stripped volumes of the foot’scomputed tomographs and magnetic resonance images could be a solution for standardization regardless of the degrees of plantar flexion.Conclusion: The exploration of volume model, accompanied by equivalent surface models, can potentially be applied toanatomical research in order to discern the morphological properties of a region or an organ.

KISTI is carrying out an e-Spine project for spinal diseases to prepare for the aged society, so-called NAP. The purpose of the study is to build a spine ontology that represents the anatomical structure and disease information which is compatible with simulation model of KISTI. The final use of the ontology includes diagnosis of diseases and setting treatment directions by the clinicians. The ontology was represented using 3D software. Twenty diseases were selected to be represented after discussions with a spine specialist. Several ontology studies were reviewed, reference books were selected for each disease and were organized in MS Excel. All the contents were then reviewed by the specialists. Altova SemanticWorks and Protégé were used to code spine ontology with OWL Full model. Links to the images from KISTI and sample images of diseases were included in the ontology. The OWL ontology was also reviewed by the specialists again with Protégé. We represented unidirectional ontology from anatomical structure to disease, images, and treatment. The ontology was human understandable. It would be useful for the education of medical students or residents studying diseases of spine. But in order for the computer to understand the ontology, a new model with OWL DL or Lite is needed.