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Evaluation of a Bricked Volume Layout for a Medical Workstation based on Java

Evaluation of a Bricked Volume Layout for a Medical Workstation based on Java. Peter Kohlmann, Stefan Bruckner, Armin Kanitsar, M. Eduard Gröller Institute of Computer Graphics and Algorithms Vienna University of Technology. Outline. Motivation Multi-planar Reformatting (MPR)

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Evaluation of a Bricked Volume Layout for a Medical Workstation based on Java

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  1. Evaluation of a Bricked Volume Layout for a Medical Workstation based on Java Peter Kohlmann, Stefan Bruckner, Armin Kanitsar, M. Eduard Gröller Institute of Computer Graphics and Algorithms Vienna University of Technology

  2. Outline • Motivation • Multi-planar Reformatting (MPR) • Results for different access patterns • MPR • Random access • Spherical access • Conclusions Peter Kohlmann

  3. Motivation • Most medical workstations: linear volume layout • Increasing size of medical volume data Main memory: limiting factor for data visualization • Better memory utilization with subdivided volumes • Evaluation for company partner: • use of bricked volume layout for medical workstation implemented in Java • performance for common access patterns to medical volume data Peter Kohlmann

  4. Bricking in a Nutshell • Medical volumes data sets: stacks of 2D images (slices) • Linear volume layout: data values stored in single array Problem: rendering of large data sets • Bricked volume layout: subdivision of volume into smaller parts (bricks) • Single brick: fixed number of data values in x-, y- and z-dimension Peter Kohlmann

  5. Multi-Planar Reformatting in a Nutshell • Important access pattern to medical volume data • Radiologists prefer to examine 2D slices • Arbitrary reformation of 2D image stack • Medical workstations display volume data in different views Peter Kohlmann

  6. Basic Algorithms BrickGeneration Image MPR Computation BrickRasterization Basic Ray Setup Brick Prefetching Brick-wise Processing Ray Propagation Peter Kohlmann

  7. Brick Generation • Efficient addressing: brick size power of two • Good choice: 64 KB (32x32x32 x 16 bit) (Grimm et al. 04, Law and Yagel 96) • Brick is simple data structure: • unique ID • min- and max-value • padding Peter Kohlmann

  8. MPR Computation • Brick-wise resampling of the volume along scan lines (rays) BrickRasterization Basic Ray Setup Brick Prefetching Brick-wise Processing Ray Propagation Peter Kohlmann

  9. MPR Computation Processing of a single brick Image generation BrickRasterization Basic Ray Setup Brick Prefetching Brick-wise Processing Ray Propagation Peter Kohlmann

  10. Results • MPR Computation • Random access • Spherical access • PC configuration • AMD Athlon 64 Dual Core Processor 4400+ • 2 GB of main memory • NVIDIA GeForce 7800 GTX with 256 MB of internal memory • Test data set: 512 x 512 x 333 Peter Kohlmann

  11. Results – MPR Computation Computation time for single slice (512 x 512) axial sagittal coronal arbitrary Peter Kohlmann

  12. Results – MPR Computation • Computation time for single slice (512 x 512) • Evaluation: • Axial and coronal: -30% • Sagittal: +30% • Randomly oriented plane: -16% • High performance gaps for linear volume layout: different memory access patterns • Utilization of bricking better data locality Peter Kohlmann

  13. Results – Random Access • Worst case scenario to access data values concerning data locality • Time to access 512 x 512 randomly distributed values • 21.4 ms (linear volume layout) • 41.4 ms (bricked volume layout) • Calculation effort to access the data value at certain position • Linear volume layout: one-level calculation • Bricked volume layout: two-level calculation Peter Kohlmann

  14. Results – Spherical Access • Definition of parameterized sphere inside volume • Simulation of region growing • Access 512 x 512 data values on parameterized sphere surface • Radius: 5 to 150 • Linear volume layout: 10.5 ms – 13.6 ms • Bricked volume layout: • No brick prefetching: 32 ms – 260 ms • Brick prefetching: 15.5 ms (constant) • reasonable performance with intelligent prefetching Peter Kohlmann

  15. Conclusions • Evaluation results for different access patterns to medical volume data • MPR • Random access • Spherical access • Benefits of bricked volume layout more pronounced for larger data sets • We recommend the application of bricked volume layout to a medical workstation based on Java Peter Kohlmann

  16. Thanks for your Attention! Peter Kohlmann

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