Koojoo Kwon

Virtual Endoscopic and Laparoscopic Exploration of Stomach Wall Based on a Cadaver's Sectioned Images

We intended to determine that virtual endoscopy and laparoscopy of the stomach based on serially sectioned cadaver images is beneficial. Therefore, the outlines between the gastric wall and lumen were traced using the new female data of the Visible Korean to build a volume model. While the outlines were expanded at appropriate thicknesses, the stomach was observed endoscopically and laparoscopically in comparison with a chosen sectioned image. Four layers (mucosa, submucosa, muscular layer, and serosa) of the stomach were discernible by their proper colors in the sectioned images. All layers except the submucosa were identified in the endoscopic and laparoscopic views by using consistent colors. The stepwise expansion of the outlines revealed thickness of each layer as well as whether the thickness was uniform. Our ideas and the Visible Korean images could be a robust resource of virtual reality learning for medical students and clinicians. Graphical Abstract

Laparoscopic and endoscopic exploration of the ascending colon wall based on a cadaver sectioned images

For realistic virtual dissection, the sectioned images of a cadaver are a desirable material because of their high resolution and real body color. After a volume model is made of the sectioned images, it can be piled or peeled at the intended thickness as if a structure’s surface is expanded and shrunken. The purpose of our study was to confirm whether laparoscopic and endoscopic exploration of the processed volume model plays a part in anatomy investigation. The ascending colon was outlined in serially sectioned images and accumulated to build a volume model. While the volume model was being piled or peeled, the ascending colon was observed laparoscopically and endoscopically in comparison with the original sectioned image. The trial efficiently demonstrated layers of the colon wall and surrounding tissues which could not be visualized by conventional macroscopic or microscopic techniques. The availability and contribution of this new method will be confirmed by application to other various organs.

GPU-accelerated 3D mipmap for real-time visualization of ultrasound volume data

Ultrasound volume rendering is an efficient method for visualizing the shape of fetuses in obstetrics and gynecology. However, in order to obtain high-quality ultrasound volume rendering, noise removal and coordinates conversion are essential prerequisites. Ultrasound data needs to undergo a noise filtering process; otherwise, artifacts and speckle noise cause quality degradation in the final images. Several two-dimensional (2D) noise filtering methods have been used to reduce this noise. However, these 2D filtering methods ignore relevant information in-between adjacent 2D-scanned images. Although three-dimensional (3D) noise filtering methods are used, they require more processing time than 2D-based methods. In addition, the sampling position in the ultrasonic volume rendering process has to be transformed between conical ultrasound coordinates and Cartesian coordinates. We propose a 3D-mipmap-based noise reduction method that uses graphics hardware, as a typical 3D mipmap requires less time to be generated and less storage capacity. In our method, we compare the density values of the corresponding points on consecutive mipmap levels and find the noise area using the difference in the density values. We also provide a noise detector for adaptively selecting the mipmap level using the difference of two mipmap levels. Our method can visualize 3D ultrasound data in real time with 3D noise filtering.

A fast 3D adaptive bilateral filter for ultrasound volume visualization

BACKGROUND AND OBJECTIVE This paper introduces an effective noise removal method for medical ultrasound volume data. Ultrasound data usually need to be filtered because they contain significant noise. Conventional two-dimensional (2D) filtering methods cannot use the implicit information between adjacent layers, and existing 3D filtering methods are slow because of complicated filter kernels. Even though one filter method utilizes simple filters for speed, it is inefficient at removing noise and does not take into account the characteristics of ultrasound sampling. To solve this problem, we introduce a fast filtering method using parallel bilateral filtering and adjust the filter window size proportionally according to its position. METHODS We devised a parallel bilateral filtering by obtaining a 3D summed area table of a quantized spatial filter. The filtering method is made adaptive by changing the kernel window size according to the distance from the ultrasound signal transmission point. RESULTS Experiments were performed to compare the noise removal and loss of original data of the anisotropic diffusion filtering, bilateral filtering, and adaptive bilateral filtering of ultrasound volume-rendered images. The results show that the adaptive filter correctly takes into account the sampling characteristics of the ultrasound volumes. CONCLUSIONS The proposed method can more efficiently remove noise and minimize distortion from ultrasound data than existing simple or non-adaptive filtering methods.

Visualization of segmented color volume data using GPU

Recently, several color volume data such as Visible Human became available for generating a realistic image. These dataset are commonly operated on CPU, however, the rendering time is time-consuming task on CPU. GPU-based volume rendering method can visualize color volume data more easily and quickly because it provides 3D texture including RGB channel. In this paper, we present the GPU-based visualization method of segmented color volume data. During the rendering stage, we need two volume datasets, color and segmented volume. However, the segmented volume requires additional memory. In our method, we use only one 3D texture in GPU. We encode three kinds of values in the 3D texture, color, segmented index and tagged values. Segmented index means the index value of internal organ. And the tagged values are the information of region of interest. We can visualize fast the color image of real human body without additional memory.

Surface models and gradually peeled volume model to explore hand structures

This study was intended to confirm whether simultaneous examination of surface and volume models contributes to learning of hand structures. Outlines of the skin, muscles, and bones of the right hand were traced in sectioned images of a male cadaver to create surface models of the structures. After the outlines were filled with selected colors, the color-filled sectioned images were stacked to produce a volume model of the hand, from which the skin was gradually peeled. The surface models provided locational orientation of the hand structures such as extrinsic and intrinsic hand muscles, while the peeled volume model revealed the depth of the individual hand structures. In addition, the characteristic appearances of the radial artery and the wrist joint were confirmed. The exploration of the volume model accompanied by equivalent surface models is synergistically helpful for understanding the morphological properties of hand structures.

Peeled and Piled Volume Models of the Stomach Made from a Cadaver's Sectioned Images

El diagnostico y el tratamiento de enfermedades del estomago requieren del conocimiento del mayor numero de detalles posible sobre su anatomia. El objetivo de este estudio, basado en secciones de imagenes de cadaver, es ofrecer a los medicos la anatomia del estomago y sus estructuras vecinas desde un nuevo punto de vista. Se utilizaron imagenes de secciones de un cadaver, de sexo masculino, sin patologia del estomago. Por segmentacion manual y automatica de interpolacion, se reconstruyo un modelo de volumen de alta calidad del estomago. El modelo fue descortezado y apilado para revelar sinteticamente el interior y exterior del estomago. Se compararon los puntos de vista anterior, posterior, derecho e izquierdo de los modelos en una seccion elegida. Las numerosas imagenes del estomago luego fueron puestas en el software de navegacion de facil uso para el profesional. Algunas de las ventajas de este estudio son que las imagenes seccionadas revelan el color real del estomago con alta resolucion; los modelos de volumen descortezados y apilados dan lugar a nuevas funciones del estomago y sus estructuras circundantes; y los modelos procesados pueden ser convenientemente navegados en el software presentado. Se espera que estos datos de imagen y el tutorial del programa sean de utilidad para la adquisicion de informacion morfologica complementaria sobre el estomago y las estructuras relacionadas.

Colonoscopy tutorial software made with a cadaver's sectioned images.

Novice doctors may watch tutorial videos in training for actual or computed tomographic (CT) colonoscopy. The conventional learning videos can be complemented by virtual colonoscopy software made with a cadavers sectioned images (SIs). The objective of this study was to assist colonoscopy trainees with the new interactive software. Submucosal segmentation on the SIs was carried out through the whole length of the large intestine. With the SIs and segmented images, a three dimensional model was reconstructed. Six-hundred seventy-one proximal colonoscopic views (conventional views) and corresponding distal colonoscopic views (simulating the retroflexion of a colonoscope) were produced. Not only navigation views showing the current location of the colonoscope tip and its course, but also, supplementary description views were elaborated. The four corresponding views were put into convenient browsing software to be downloaded free from the homepage (anatomy.co.kr). The SI colonoscopy software with the realistic images and supportive tools was available to anybody. Users could readily notice the position and direction of the virtual colonoscope tip and recognize meaningful structures in colonoscopic views. The software is expected to be an auxiliary learning tool to improve technique and related knowledge in actual and CT colonoscopies. Hopefully, the software will be updated using raw images from the Visible Korean project.

Improved Software to Browse the Serial Medical Images for Learning

The thousands of serial images used for medical pedagogy cannot be included in a printed book; they also cannot be efficiently handled by ordinary image viewer software. The purpose of this study was to provide browsing software to grasp serial medical images efficiently. The primary function of the newly programmed software was to select images using 3 types of interfaces: buttons or a horizontal scroll bar, a vertical scroll bar, and a checkbox. The secondary function was to show the names of the structures that had been outlined on the images. To confirm the functions of the software, 3 different types of image data of cadavers (sectioned and outlined images, volume models of the stomach, and photos of the dissected knees) were inputted. The browsing software was downloadable for free from the homepage (anatomy.co.kr) and available off-line. The data sets provided could be replaced by any developers for their educational achievements. We anticipate that the software will contribute to medical education by allowing users to browse a variety of images.

Peeled and Piled Volume Models of the Kidney that Show Actual Morphology

Current learning tools such as photographs, cadavers, and computer models are not sufficient for learning the comprehensive anatomy of the kidney and its surroundings. The objective of this research was to aid medical students by presenting tutorial software that contains peeled and piled volume models of the kidney. The sectioned images of donated female cadaver (age at death, 26 years; cause of death, stomach cancer; kidney pathology, none) were stacked to reconstruct three-dimensional volume model (voxel size, 0.2 mm) (1). Peeling and piling of the model were continuously carried out (intervals, 0.4 mm) to explore the inside and outside of the kidney (2).