Interactive Visualization of the Largest Radioastronomy Cubes

3D visualization is an important data analysis and knowledge discovery tool, however, interactive visualization of large 3D astronomical datasets poses a challenge for many existing data visualization packages. We present a solution to interactively visualize larger-than-memory 3D astronomical data cubes by utilizing a heterogeneous cluster of CPUs and GPUs. The system partitions the data volume into smaller sub-volumes that are distributed over the rendering workstations. A GPU-based ray casting volume rendering is performed to generate images for each sub-volume, which are composited to generate the whole volume output, and returned to the user. Datasets including the HI Parkes All Sky Survey (HIPASS - 12 GB) southern sky and the Galactic All Sky Survey (GASS - 26 GB) data cubes were used to demonstrate our framework's performance. The framework can render the GASS data cube with a maximum render time < 0.3 second with 1024 x 1024 pixels output resolution using 3 rendering workstations and 8 GPUs. Our framework will scale to visualize larger datasets, even of Terabyte order, if proper hardware infrastructure is available.Comment: 15 pages, 12 figures, Accepted New Astronomy July 201

Interactive 3D Visualization of a Large University Campus over the Web

Nowadays, with the rise and generalized use of web applications and graphical hardware evolution, one of the most interesting problems deals with realistic real-time visualization of virtual environments on web browsers. This paper shows an on-line application to dynamically visualize a large campus on the World Wide Web. The application focuses on a smooth walk through a large 3D environment in real-time as an alternative way to index geographically related information. This way, contents are continuously filtered based on viewpoint¿s position. This can be made thanks to the availability of different models corresponding to different levels of detail (LOD) for each modeled building. A server storage model has been purposed including all models, compound of meshes, textures and information. The technique is based on an algorithm that performs a progressive refining of the models, according to the distance from the viewpoint.Vendrell Vidal, E.; Sanchez Belenguer, C. (2011). Interactive 3D Visualization of a Large University Campus over the Web. International Journal of Computer Information Systems and Industrial Management Applications. 3:514-521. http://hdl.handle.net/10251/35020S514521

Feature-preserving downsampling for medical images

In the medical imaging field, interactive direct volume rendering of large volume datasets is a challenging task. Multi-resolution techniques deal with this problem by downsampling the original dataset to produce coarser representations. We present an evaluation of different downsampling filters with respect to their effectiveness at preserving details of the original dataset. Moreover, we propose a new Gaussian-based filter that produces quality lower-resolution representations and preserves small features that are prone to disappear.Peer ReviewedPostprint (author's final draft

Volumetric Medical Images Visualization on Mobile Devices

Volumetric medical images visualization is an important tool in the diagnosis and treatment of diseases. Through history, one of the most dificult tasks for Medicine Specialists has been the accurate location of broken bones and of the damaged tissues during Chemotherapy treatment, among other applications; like techniques used in Neurological Studies. Thus these situations enhance the need of visualization in Medicine. New technologies, the improvement and development of new hardware as well as software and the updating of old ones for graphic applications have resulted in specialized systems for medical visualization. However the use of these techniques in mobile devices has been poor due to its low performance. In our work, we propose a client-server scheme, where the model is compressed in the server side and is reconstructed in a nal thin-client device. The technique restricts the natural density values to achieve good bone visualization in medical models, transforming the rest of the data to zero. Our proposal uses a tridimensional Haar Wavelet Function locally applied inside units blocks of 16x16x16, similar to the Wavelet Based 3D Compression Scheme for Interactive Visualization of Very Large Volume Data approach. We also implement a quantization algorithm which handles error coeficients according to the frequency distributions of these coe cients. Finally, we made an evaluation of the volume visualization; on current mobile devices .We present the speci cations for the implementation of our technique in the Nokia n900 Mobile Phone

Feature-preserving Reduction and Visualization of Industrial CT data using GLCM texture analysis and Mass-spring Model Deformation

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 8. 신영길.본 논문에서는 3D 볼륨 데이터에서 중요한 영역을 보존하면서 크기를 줄이는 방법을 제안한다. 볼륨 데이터에서 어느 부분이 중요한 영역인지를 결정하기 위해 질감 분석 방법 중 하나인 GLCM 균일도를 이용한 중요도 측정 모델을 제안하고, 이를 기반으로 한 MSM 기반의 볼륨 변형을 수행한다. 중요도가 반영된 볼륨 변형 과정을 통해, 중요한 영역은 상대적으로 크기가 확장되는 반면, 덜 중요한 영역은 줄어들게 된다. 이로 인해, 일반적으로 손실률이 높은 균일 다운샘플링을 이용한 압축 후에도 작은 크기의 중요한 특징점들이 손실되지 않고 보존될 수 있다. 실측 산업 영상 데이터를 이용한 실험을 통해, 그냥 균일 다운샘플링을 이용한 압축 결과에서는 사라진 작은 기공이나 수축 균열 형태의 결함 영역이 제안 방법에서는 보존되는 것을 확인할 수 있었다. 이 변형 볼륨을 원래 형태로 가시화하기 위해선 역변형 과정을 추가로 수행해야 하지만, 이 계산은 가시화 과정에 간단하게 추가할 수 있으며, 결과를 얻기 위한 소요시간에 유의미한 영향을 미치지 않는다.Non-destructive testing is a method which examines the internal structures of industrial components such as various machine parts without dissecting them. Recently, 3D CT based analysis enables more accurate inspection than traditional X-ray based tests. However, manipulating volumetric data acquired by CT is still challenging due to its huge size of the volume data. This dissertation proposes a novel method that reduces the size of 3D volume data while preserving important features in the data. Our method quantifies the importance of features in the 3D data based on gray level co-occurrence matrix (GLCM) texture analysis and represents the volume data using a simple mass-spring model. According to the measured importance value, blocks containing important features expand while other blocks shrink. After deformation, small features are exaggerated on deformed volume space, and more likely to survive during the uniform volume reduction. Experimental results showed that our method well preserved the small features of the original volume data during the reduction without any artifact comparing with the previous methods. Although additional inverse deformation process was required for the rendering of the deformed volume data, the rendering speed of the deformed volume data was much faster than that of the original volume data.초록 i 목차 iii 그림 목차 vi 표 목차 x 1장 서론 1 1.1 볼륨 렌더링 1 1.2 비파괴검사 2 1.3 연구 내용 4 1.4 논문의 구성 6 2장 관련 연구 7 2.1 볼륨 렌더링 알고리즘 7 2.1.1 볼륨 데이터의 특성 7 2.1.2 표면 추출 기법 8 2.1.3 직접 볼륨 렌더링 10 2.2 압축 볼륨 렌더링 17 2.2.1 벡터 양자화 18 2.2.2 변환 부호화 19 2.2.3 다중-해상도 기반 기법 23 2.2.4 볼륨 변형 기반 방법 25 2.3 질량-스프링 기반 볼륨 변형 모델 27 2.4 산업용 CT 영상의 중요 특징점 측량 방법 30 3장 중요도 측정 기법 32 3.1 명암도 동시발생 행렬 32 3.2 GLCM 균일도 기반 중요도 모델 36 3.3 공기 영역 제거 44 4장 볼륨 변형, 축소 및 가시화 47 4.1 질량-스프링 모델 기반 볼륨 변형 47 4.2 볼륨 축소 54 4.3 역변형 및 렌더링 55 5장 실험 및 결과 58 5.1 화질 평가 60 5.2 속도 평가 65 5.3 파라미터 연구 69 6장 결론 74 6.1 요약 74 6.2 향후 연구 75 참고문헌 77 Abstract 83Docto