직접 볼륨 렌더링을 위한 CNN 기반 TF 색상 매핑

국문 초록 (Abstract)

직접 볼륨 렌더링은 볼륨 표면의 연산 없이 2차원 공간에 투영하여 렌더링 한다. 직접 볼륨 렌더링에서 전이함수(TF)는 볼륨에 색상과 투명도와 같은 광원 특성을 할당하는데 활용된다. 하지만 초보자가 TF를 조작하여 볼륨데이터를 파악하고 색상을 할당하기까지 오랜 시간이 필요합니다. 본 논문에서는 직관적인 볼륨 렌더링을 위해 인터넷에서 수집한 이미지를 사용하여 TF에 볼륨의 색상을 매핑하는 접근 방식을 제안한다. 또한 우리는 K-means 클러스터링을 활용한 색상 추출 방법을 토의한다.

다국어 초록 (Multilingual Abstract)

Direct Volume Rendering(DVR) renders by projecting data into a two-dimensional space without calculating the volume surfaces. In DVR, the transfer function(TF) assigns light properties such as color and transparency to the volume. However, it takes a long time for beginners to manipulate TF to understand volume data and assign colors. This paper proposes an approach to colorize the volume using sample images for intuitive volume rendering. We also discuss color extraction methods using K-means clustering.

목차 (Table of Contents)

• 요약
• Abstract
• 1. 서론
• 2. 관련연구
• 3. CNN 기반 TF 색상 매핑
• 4. 결과 및 색상 추출 방법에 관한 토의
• 5. 결론 및 향후연구
• References

참고문헌 (Reference)

1 T. Fogal, "an Architecture for Large Scale Volume Rendering" 2010

2 H. Guo, "Wysiwyg(what you see is what you get)volume visualization" 17 (17): 2106-2114, 2011

3 B. Ma, "Volumetric feature-based classification and visibility analysis for transfer function design" 24 (24): 3253-3267, 2018

4 M. Haidacher, "Volume visualization based on statistical transfer-function spaces" 17-24, 2010

5 W. Serna-Serna, "Volume rendering by stochastic neighbor embedding-based 2d transfer function building" 618-626, 2017

6 R. A. Drebin, "Volume rendering" 65-74, 1988

7 T. Pfaffelmoser, "Visualizing the positional and geometrical variability of isosurfaces in uncertain scalar fields" 30 (30): 951-960, 2011

8 P. Sereda, "Visualization of boundaries in volumetric data sets using lh histograms" 12 (12): 208-218, 2006

9 H. Childs, "Visit : An enduser tool for visualizing and analyzing very large data" 357-372, 2012

10 C. D. Correa, "Visibility histograms and visibility-driven transfer functions" 17 (17): 192-204, 2011

11 S. Martin, "Using a depth heuristic for light field volume rendering" 1 : 134-144, 2019

12 S. Castro, "Transfer function specification for the visualization of medical data" Vienne University of Technology 1998

13 C. Correa, "The occlusion spectrum for volume classification and visualization" 15 (15): 1465-1472, 2009

14 J. J. Caban, "Texture-based transfer functions for direct volume rendering" 14 (14): 1364-1371, 2008

15 R. Maciejewski, "Structuring feature space: A non-parametric method" 15 (15): 1473-1480, 2009

16 J. M. Kniss, "Statistically quantitative volume visualization" 287-294, 2005

17 P. Ljung, "State of the art in transfer functions for direct volume rendering" 35 (35): 669-691, 2016

18 S. Roettger, "Spatialized transfer functions" 271-278, 2005

19 C. Correa, "Size-based transfer functions : A new volume exploration technique" 14 (14): 1380-1387, 2008

20 M. A. Selver, "Semiautomatic transfer function initialization for abdominal visualization using self-generating hierarchical radial basis function networks" 15 (15): 395-409, 2009

21 G. Kindlmann, "Semi-automatic generation of transfer functions for direct volume rendering" 79-86, 1998

22 H. Guo, "Scalable multivariate volume visualization and analysis based on dimension projection and parallel coordinates" 18 (18): 1397-1410, 2012

23 J. Kniss, "Multidimensional transfer functions for interactive volume rendering" 8 (8): 270-285, 2002

24 H. Guo, "Multi-dimensional transfer function design based on flexible dimension projection embedded in parallel coordinates" 19-26, 2011

25 C. Lundstrom, "Multi-Dimensional Transfer Function Design Using Sorted Histograms" The Eurographics Association 2006

26 L. Wang, "Modified dendrogram of attribute space for multidimensional transfer function design" 18 (18): 121-131, 2012

27 C. Lundstrom, "Local histograms for design of transfer functions in direct volume rendering" 12 (12): 1570-1579, 2006

28 Y. Wu, "Interactive transfer function design based on editing direct volume rendered images" 13 (13): 1027-1040, 2007

29 R. Bramon, "Information theory-based automatic multimodal transfer function design" 17 (17): 870-880, 2013

30 S. Lan, "Improving separability of structures with similar attributes in 2d transfer function design" 23 (23): 1546-1560, 2017

31 S. Kim, "Image-Based TF Colorization With CNN for Direct Volume Rendering" 9 : 124281-124294, 2021

32 Z. Wang, "Image quality assessment : from error visibility to structural similarity" 13 (13): 600-612, 2004

33 C. R. Salama, "High-level user interfaces for transfer function design with semantics" 12 (12): 2006

34 T. He, "Generation of transfer functions with stochastic search techniques" 227-234, 1996

35 G. Kindlmann, "Curvature-based transfer functions for direct volume rendering: Methods and applications" 513-520, 2003

36 J. Hladuvka, "Curvature-based transfer functions for direct volume rendering" 58-65, 2000

37 J. Li, "Classification for volume rendering of industrial ct based on moment of histogram" 913-918, 2007

38 P. Sereda, "Automating transfer function design for volume rendering using hierarchical clustering of material boundaries" 243-250, 2006

39 I. Fujishiro, "Automating transfer function design for comprehensible volume rendering based on 3d field topology analysis" 467-563, 1999

40 R. Maciejewski, "Abstracting attribute space for transfer function exploration and design" 19 (19): 94-107, 2013

41 H. Akibay, "A tri-space visualization interface for analyzing time-varying multivariate volume data" 115-122, 2007

42 S. Arens, "A survey of transfer functions suitable for volume rendering" 77-83, 2010

43 S. Wesarg, "2d histogram based volume visualization : combining intensity and size of anatomical structures" 5 (5): 655-666, 2010