Hessian-based Multiscale Filtering: Volume Rendering Gallery of 3D Medical Images

• Sato Y, et al, Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images, Medical Image Analysis, vol. 2, no. 2, pp. 143-168, 1998.
  
• Sato Y, et al, Tissue classification based on 3D local intensity structures for volume rendering, IEEE Transactions on Visualization and Computer Graphics, vol. 6, no. 2, pp. 160-180, 2000.
  

Abstract: 3D image filters for the enhancement of specific local intensity structures such as line and sheet, and their application to tissue classification for volume rendering are demonstrated. Multi-channel classification is performed by combining different 3D image filter outputs. The resulted method significantly enlarges the scope of volume rendering, especially in the medical domain. We show the usefulness of the method for various visualization problems.

Requirements for Visualization of 3D Medical Images
Minimize Burden of Interactive Segmentation
Maximize Objectivity and Reality

Conventional Volume Rendering
Single-Channel Tissue Classification Using Original Graylevel Only

Our Approach: 3D Image Filter + Volume Rendering
3D Image Filters for Enhancement of Specific Tissues
Multi-Channel Tissue Classification by Combining Different 3D Image Filter Outputs

Volume Rendering Gallery

The PDF file of the papar on this topic (IEEE Transactions on Visualization and Computer Graphics, 6(2): 160-180 2000) is available (click here for PDF file!). All the images in this page were created using the volpack library developped by P. Lacroute and M. Levoy at Stanford University.

Yoshinobu Sato is with the Division of Interdisciplinary Image Analysis, Osaka University Medical School. The volume rendered images were partly created while he was staying as a visiting researcher at the Surgical Planning Laboratory (Director: Ron Kikinis), Department of Radiology, Brigham and Women's Hospital and Harvard Medical School in 1996 and 1997.

Collaborators: Carl-Fredrik Westin, Abhir Bhalerao, Shin Nakajima, Nobuyuki Shiraga, Shigeyuki Yoshida, Gary Zientara, and Ron Kikinis.

Acknowledgement: Yoshi Sato would like to specially thank Shin Nakajima because his volume rendering images created by Macintosh inspired me to do this work and he has been continuously giving me the inspiration of the research.

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