Performance of Hardware Accelerated Bone Segmentation on 4DCT Images



Results generated from testing the performance of a bone segmentation algorithm
implemented in both hardware and software for segmenting bone in medical

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:

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 available5 Jan 2021
PublisherUniversity of Strathclyde
Date of data production1 Sept 2019 - 3 Sept 2019

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