Projects per year
Description
Results generated from testing the performance of a bone segmentation algorithm
implemented in both hardware and software for segmenting bone in medical
images.
The bone segmentation algorithm used was one described by Haas et al.
(doi: 10.1088/0031-9155/53/6/017). The algorithm was implemented in full in
software and a simplified version was developed for hardware implementation,
which was implemented in both hardware and software. Details of these
implementations can be obtained from the following DOI:
https://doi.org/10.15129/1a667dbc-8202-443d-a52b-45b5f8b498d2.
The software algorithms were executed on a 2.6GHz Intel Core i5-3230M CPU,
while the hardware system was implemented on a Xilinx Zynq Z7020 device on an
AvNet ZedBoard development board.
Image data in the form of 4-dimensional computed tomography (4DCT) scans of a
Modus Medical QUASAR Programmable Respiratory Motion Phantom (Modus Medical
Devices Inc. London, ON) were obtained from Edinburgh Cancer Centre (n=8) and
used as the input data. Each of the datasets contained fifteen 3D image volumes
that were each segmented.
The time taken to process each image volume and each slice of each image volume
was recorded for each of the three implementations.
See the README file for further details.
implemented in both hardware and software for segmenting bone in medical
images.
The bone segmentation algorithm used was one described by Haas et al.
(doi: 10.1088/0031-9155/53/6/017). The algorithm was implemented in full in
software and a simplified version was developed for hardware implementation,
which was implemented in both hardware and software. Details of these
implementations can be obtained from the following DOI:
https://doi.org/10.15129/1a667dbc-8202-443d-a52b-45b5f8b498d2.
The software algorithms were executed on a 2.6GHz Intel Core i5-3230M CPU,
while the hardware system was implemented on a Xilinx Zynq Z7020 device on an
AvNet ZedBoard development board.
Image data in the form of 4-dimensional computed tomography (4DCT) scans of a
Modus Medical QUASAR Programmable Respiratory Motion Phantom (Modus Medical
Devices Inc. London, ON) were obtained from Edinburgh Cancer Centre (n=8) and
used as the input data. Each of the datasets contained fifteen 3D image volumes
that were each segmented.
The time taken to process each image volume and each slice of each image volume
was recorded for each of the three implementations.
See the README file for further details.
Date made available | 5 Jan 2021 |
---|---|
Publisher | University of Strathclyde |
Date of data production | 1 Sept 2019 - 3 Sept 2019 |
Projects
- 1 Finished
-
Medical Devices Doctoral Training Centre Renewal | Robinson, Fraser
Crockett, L. (Principal Investigator), Stewart, R. (Co-investigator) & Robinson, F. (Research Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/10/13 → 4/03/21
Project: Research Studentship - Internally Allocated
Datasets
-
Performance of Hardware Accelerated Bone Segmentation with Noise Reduction on 4DCT Images
Robinson, F. (Creator), Crockett, L. H. (Contributor), Stewart, R. (Contributor), Nailon, W. H. (Contributor) & McLaren, D. (Contributor), University of Strathclyde, 11 Jan 2021
DOI: 10.15129/89d99e2a-a2c6-4f82-9626-b849fc93e6c2
Dataset
-
Performance of Hardware Accelerated Bone Segmentation
Robinson, F. (Creator), Crockett, L. H. (Contributor), Stewart, R. (Contributor), Nailon, W. H. (Contributor) & McLaren, D. (Contributor), University of Strathclyde, 10 Aug 2019
DOI: 10.15129/1a667dbc-8202-443d-a52b-45b5f8b498d2
Dataset