3d visualisation of medical images

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3D visualization of 2D Medical Imaging Data By Shashank Singh 2000 0048 Project Guide: Dr. U. S. Tiwary Medical Image Processing Data Set Credit

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How to do 3D visualisation of 2D images and recostruct human organs in 3D

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Page 1: 3D visualisation of medical images

3D visualization of 2D Medical Imaging Data

ByShashank Singh

2000 0048

Project Guide: Dr. U. S. Tiwary

Medical Image Processing

Data Set Credit

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A brief Introduction

3D viewing system for

- easy visualization and interpretation.

- handle larger amount data.

- education and real life medical applications.

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The project aims at surface visualization and 3-dimensional viewing of anatomical CT/MRI slices. Working as a part of ‘Fusion of Multi-Modal Medical Imaging Data’ project, I would provide support for 3d viewing of object of interest from various 2d data modalities like CT, MRI slices and anatomical section images.

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Steps• 1. Obtain the data set• 2. Extract the compressed files• 3. Convert the data files in RAW format to suitable image format

(.PNG)• 4. Crop, shrink or expand the images to fit onto one another

precisely.• 5. Perform threshold and segmentation to retain the object of

interest and remove unwanted• surrounding regions and background.• 6. Interpolate to obtain the missing slices.• 7. Perform Ray-Casting on the slices to obtain 3D surface

visualization of the objects• present in the slices.• 8. Apply false coloring for better visual perception.

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Visualization options

• Control point based Rendering of voxels.

• Marching cube

• Ray casting

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Problems in the methods

• Volume rendering : blocky image, loss of features.

• Marching cube: false positive/negative local artifacts.

• Ray casting: expensive.

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Ray Casting

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Marching Cube

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BASICS AND TERMINOLOGY:Object: The original physical object under study. This may be a

particular organ in the body, a human made device, a pathological entity etc.

Object System: A collection of objects. For example the brain is an object system made up of object like – the white matter, the gray matter the Cerebrospinal fluid (CSF).

Body Region: A finite region of 3D space within which the object system of study is embedded.

Imaging Device: A device used that produces a digital image of the body region with its object contents E.g. CT scanners, MRI devices

Pixel, Voxel: In a digital form the body region is virtually partitioned into small abutted cubical volume elements and the imaging device estimated an aggregate of property if the material within each such element. The volume element is called VOXEL. The 2D analog of voxel is a pixel (picture element).

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Rendering by scene based method consists following three basic steps:

• Projection.

• Hidden part removal.

• Shading.

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Inefficiency

• The need to sample point along the ray,

• The need to interpolate,

• The need to store the entire scene in memory.

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Results

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Sagittal views from axial slices

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Coronal view

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View at 45 degree

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Skin visualization from cryo-sections

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• TIME LINE:• November – December:• Implemented basic operations like Gamma Correction, Noise Removal, Histogram Equalization, FFT.• Work on building an interface for preprocessing the images.• Inter-Slice Interpolation implemented.• January - February: • Collect resources, study and explore about different 3D visualization methods, their utility in case of

medical images.• Learn from similar projects at other universities – their experiences and difficulties.• Search for suitable data source. Finally found the repository at NLM.• March:• 5th March 2004, applied for license to use data set from VHP at NLM.• 10th March 2004, began data download from the NLM ftp server.• Trying Marching Cube and Surface Rendering Algorithm but had to dropped them later• Switched to Ray-Casing• April 2nd – 15th • - Extracted compressed data set files..• Converted raw files to .PNG format.• Segmented CT slices to obtain skull.• Obtained image intensity value profiles along a line through the middle of the CT, MRI and Cryo-section

images.• Finished with implementation of Ray Casting.• April 12th – 30th • Tested implementation on test images.• Applied the method to real CT slice data set.• Obtained first complete skull 3D surface after 400s.• Improved upon the implementation to bring down the rendering time to 220s.• Applied method to incorporate effect of pixel values variations and the variations in lighting due to depth

into the rendered surface.• Extended method to color anatomical cryo-sections.• Completed Male and Female Cadaver Data set download over a period of 50 days at about 30 KBps

average download speed.

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Stacked slices

Final Models

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Resources

• Books

3D Imaging in Medicine

Edited by: Jayaram K. Udupa, Ph.D.University of PennsylvaniaPhiladelphia, PA

Gabor T. Herman, Ph.D. University of PennsylvaniaPhiladelphia, PA

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Computer Graphics: Principles and Practice

by:James D. Foley, Andries van Dam, Steven K. Feiner, John F. Hughes

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Resources

• Web

-The National Library of Medicine's Visible Human Project.

- IEEE Xplore.

- GE Medical Systems.http://www.gemedicalsystems.com

Visualization Tool Kit resource page.

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Thanking youShashank