Serially Sectioned Images of the Whole Body (Eighth Report: Segmentation of the Upper Limb's Structures) / 대한해부학회지

Whole body of a Korean male cadaver was serially milled to make sectioned images. Segmentation of various anatomical structures can expand the utilization of the sectioned images such as three-dimensional (3D) reconstruction of the structures of real human. Following previous outlining of lower limb's structures, we decided to make segmented images of upper limb's structures in detail. Ninety-one structures (a skin, 32 bones, 49 muscles, 6 arteries, and 3 nerves) in the left upper limb were segmented in 628 sectioned images. While doing this, we developed more efficient technique for segmentation. To draw the outlines of various structures more quickly, sectioned images were filtered first and then outlines were drawn by 'quick selection' tool and other tools on the Photoshop. Also, outlines were automatically generated by interpolation using Combustion software. We made coronal and sagittal segmented images, browsing software of the serially sectioned images, volume 3D images, and surface 3D images for verifying segmentation. These segmented and sectioned images of the upper limb are expected to help other researchers make 3D images and various software of upper limb and to have widespread applications in both medical learning and research.

Unfolding for Color Volume Dataset Using the Difference of Segmented Contours / 대한의료정보학회지

OBJECTIVE: Unfolding is a rendering method to visualize organs at a glance by virtually incising them. Although conventional methods exploit gray-scale volume datasets such as CT or MR images, we use the Visible Korean Human dataset preserving actual color. This can be helpful for the study of anatomical knowledge. Segmented images of Visible Korean Human dataset store the boundary of organs. Since medical experts manually perform the segmentation from anatomical color images, it is very time-consuming. In general, therefore, some images selectively sampled with interval from entire color images are segmented. When we generate a segment volume dataset with the selected images, final results are deteriorated due to lack of segmentation information for missed images. In this paper, we solve this problem by generating intermediate images without performing a manual segmentation. METHODS: Firstly, after comparing differences of organ's contours in between two consecutive segmented images, we represent the differences as a user-defined value in the intermediate images. This procedure is repeated for all pairs of manually segmented images to reconstruct entire volume data consist of manually segmented images and their intermediate images. In rendering stage, we perform the radial volume ray casting along with the central path of target organ. If a ray reaches to a region having the user-defined values, we advance over the region without compositions to the boundary of that region. Then the color composition is begun by performing backtracking, since the advanced region is regarded to the thickness of it. RESULTS: As a result, we can produce high quality unfolding images for the stomach, colon, bronchus, and artery of the Visible Korea Human dataset. CONCLUSION: Since our approach can be applied to virtual dissection including actual human colors, it is helpful for the endoscopy and anatomy studies.

Three Dimensional Automatic Surface Reconstruction Software / 대한의료정보학회지

OBJECTIVE: After drawing and stacking contour of structures, which are identifed in the serially sectioned images, three-dimensional (3D) images can be made by surface reconstruction. The 3D images can be selected and rotated in a real time. The purpose of this research is to compose software of automatic surface reconstruction for making 3D images. METHODS: Contours of 55 structures in the 613 magnetic resonance images of whole body were drawn to make segmented images. We composed automatic software for stacking contours of a structure, for converting the contours into polygons, and for connecting vertices of the neighboring polygons to fill gaps between polygons with triangular surfaces. The surface reconstruction software was excuted to make 3D images of 55 structures. RESULTS: Virtual dissection software, on which 3D images could be selected and rotated, was composed. CONCLUSION: For other research, this like program can be composed for automatic surface reconstruction; several kinds of commercial software can be used for manual or automatic surface reconstruction. Investigators might choose one of the methods in consideration of their only circumstances.

Serial Slice Images and Segmented Images of the Brainstem for Recognizing the Stereoscopic Morphology of its Nuclei and Tracts / 체질인류학회지

The purpose of this research is to present the serial slice images and segmented images of the human brainstem to make the three-dimensional (3D) images, which are helpful in recognizing stereoscopic morphology of the brainstem components. A brainstem was taken out from a cadaver. The brainstem was embedded with paraffin to make brainstem block. The brainstem block was serially sectioned and digitalized to make slice images. In the slice images, 28 brainstem components including several nuclei and tracts were segmented to make segmented images. The segmented images were volume-reconstructed to make 3D images. One hundred forty-three couples of serial slice images and segmented images with 0.5 mm intervals, 360 x 88 resolution, 0.125 mm pixel size, and 8 bits gray were achieved. 3D images of the brainstem components were sectioned and rotated. The serial slice images and segmented images were verified by the result that coronal images, sagittal images, and 3D images of the brainstem were not distorted. The serial slice images and segmented images of the brainstem, which were prepared in this research, will be presented to the world. The images are expected to be used for other researchers to make 3D images and virtual dissection software which are helpful in recognizing stereoscopic morphology of the brainstem components.

Serially Sectioned and Segmented Images of the Mouse for Learning Mouse Anatomy / 대한해부학회지

Mouse anatomy is fundamental knowledge for researchers who perform biomedical experiments with mice. The purpose of our research is to present the serially sectioned images and segmented images of the mouse to produce three-dimensional images of the mouse, which are helpful in learning mouse anatomy. Using a cryomacrotome, a couple of male and female mice were transversely serially sectioned at 0.5 mm intervals to make sectioned surfaces. The sectioned surfaces were digitalized to make serially sectioned images. In the serially sectioned images of the female mouse, 14 structures including skin and bones were semi-automatically segmented on Adobe Photoshop software to make segmented images. The serially sectioned images and segmented images were stacked to make sagittal and coronal images, which were used for verifying the serially sectioned images and segmented images. In this ongoing research, the segmented images of male mouse will be added. All serially sectioned images and segmented images of the mouse will be presented worldwide. These images are expected to be used by many researchers for making three-dimensional images and virtual dissection software of the mouse, which are helpful in comprehending the stereoscopic morphology of the mouse's structures.

Three Dimensional MRI and Software for Studying Normal Anatomical Structures of an Entire Body

For identifying the pathological findings in magnetic resonance images (MRIs), normal anatomical structures in MRIs should be identified in advance. For studying the anatomical structures in MRIs, a learning tool that includes the followings is necessary. First, MRIs of the entire body; second, horizontal, coronal, and sagittal MRIs; third, segmented images corresponding to the MRIs; fourth, three dimensional (3D) images of the anatomical structures in the MRIs; fifth, software incorporating the MRIs, segmented images, and 3D images. Such a learning tool, however, is hard to obtain. Therefore, in this research, such a learning tool which helps medical students and doctors study the normal anatomical structures in MRIs was made as follows. A healthy young Korean male adult with standard body shape was selected. Six hundred thirteen MRIs of the entire body were scanned (slice thickness 3 mm, interslice gap 0 mm, field of view 480 mm x 480 mm, resolution 512 x 512, T1 weighted), and transferred to the personal computer. Sixty anatomical structures in the MRIs were segmented to make segmented images. Coronal, sagittal MRIs and coronal, sagittal segmented images were made. On the basis of the segmented images, forty-seven anatomical structures' 3D images were made by manual surface reconstruction method. Software incorporating the MRIs, segmented images, and 3D images was composed. This learning tool that includes horizontal, coronal, sagittal MRIs of the entire body, corresponding segmented images, 3D images of the anatomical structures in the MRIs, and software is expected to help medical students and doctors study the normal anatomical structures in MRIs. This learning tool will be presented worldwide through Internet or CD titles.

Manufacture of the Serially Sectioned Images of the Whole Body (Third Report: Methods for Manufacture of the Segmented Images, Coronal Segmented Images, and Sagittal Segmented Images) / 대한해부학회지

While three dimensional (3D) images of the whole body can be reconstructed by using the serially sectioned images, 3D image of each anatomical structure can be reconstructed by using the segmented images. In this research, outlines of skin, bones, liver, lungs, kidneys, urinary bladder, heart, and brain in the anatomical images were decided to segment, and luminal outlines of digestive tract, respiratory tract, and arteries were decided to segment too. On the Adobe Photoshop, selections were semiautomatically drawn along outlines of the anatomical structures and semiautomatically corrected using magnetic lasso tool. Successively, selections were manually corrected either using lasso tool or through work path. The selections were filled with colors to make segmented images. By stacking rows and columns of the segmented images, coronal and sagittal segmented images were made. The coronal and sagittal segmented images were observed to find incorrect segmented images, which were revised. 8,507 segmented images with 0.2 mm intervals, 3,040x2,008 resolution, 0.2 mm pixel size, and 8 bits color depth were achieved, so that file size of 1 segmented image and 8,507 segmented images was 5.8 Mbytes and 48.3 Gbytes, respectively. These segmented images will be the basis for the development of 3D images of the anatomical structures and software of virtual dissection and virtual endoscopy, which are helpful in studying anatomy and endoscopy.

Three-Dimensional Images and Software for Studying Anatomical Structures in MRIs / 체질인류학회지

Medical students and doctors should study the appearance of normal anatomical structures in the magnetic resonance images (MRIs). For this purpose, horizontal, coronal, sagittal MRIs of a healthy entire body and corresponding segmented images were prepared. However, it is inconvenient to select interesting MRIs and segmented images; and it is difficult to understand how stereoscopic anatomical structures appear in the MRIs. Therefore, in this research, a software, on which interesting MRIs can be conveniently displayed among the horizontal, coronal, sagittal MRIs and corresponding segmented images can be displayed together, was composed. And after stacking the segmented images, three-dimensional (3D) image of each anatomical structure was manually reconstructed by surface rendering. Then another software, on which interesting 3D images of anatomical structures can be displayed and rotated, was composed too. These softwares are expected to help medical students and doctors understand normal anatomical structures in the MRIs and read pathological findings in the MRIs of patients.