3D visualization to assist iterative object definition from medical images
نویسندگان
چکیده
In medical imaging, many applications require visualization and/or analysis of three-dimensional (3D) objects (e.g. organs). At same time, object definition often requires considerable user assistance. In this process, objects are usually defined in an iterative way and their visualization during the process is very important to guide the user's actions for the next iteration. The usual procedure provides slice visualization during object definition (segmentation) and 3D visualization afterward. In this paper, we propose and evaluate efficient methods to provide 3D visualization during iterative object definition. The methods combine the differential image foresting transform for segmentation with voxel splatting/ray casting for visualization.
منابع مشابه
A Hybrid Method for Segmentation and Visualization of Teeth in Multi-Slice CT scan Images
Introduction: Various computer assisted medical procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries require automatic quantification and volumetric visualization of teeth. In this regard, segmentation is a major step. Material and Methods: In this paper, inspired by our previous experiences and considering the anatomical knowledge of teeth and jaws, we prop...
متن کاملVolume-Rendering-Based Interactive 3D Measurement for Quantitative Analysis of 3D Medical Images
3D medical images are widely used to assist diagnosis and surgical planning in clinical applications, where quantitative measurement of interesting objects in the image is of great importance. Volume rendering is widely used for qualitative visualization of 3D medical images. In this paper, we introduce a volume-rendering-based interactive 3D measurement framework for quantitative analysis of 3...
متن کاملSegmentation Assisted Object Distinction for Direct Volume Rendering
Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an ...
متن کامل3D Scene and Object Classification Based on Information Complexity of Depth Data
In this paper the problem of 3D scene and object classification from depth data is addressed. In contrast to high-dimensional feature-based representation, the depth data is described in a low dimensional space. In order to remedy the curse of dimensionality problem, the depth data is described by a sparse model over a learned dictionary. Exploiting the algorithmic information theory, a new def...
متن کاملOptimization of Reconstruction of 2D Medical Images Based on Computer
Computer 3D reconstruction consisting of reconstruction of 3D point clouds and images plays an important role in computer graphics, computer image processing and computer vision research. Image based 3D reconstruction includes reconstruction of single image and multiple images. Compared to obtain 3D mode by modeling software or scan tester traditionally, image-based 3D reconstruction is feature...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
دوره 30 4 شماره
صفحات -
تاریخ انتشار 2006