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Evaluation of Bricked Volume Layout for Medical Workstation in Java

Explore the benefits of bricked volume layout in Java for medical workstations, improving memory utilization and performance for various access patterns.

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Evaluation of Bricked Volume Layout for Medical Workstation in 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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