Performance of Hardware Accelerated Bone Segmentation

Dataset

Description

Hardware, software and 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.

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.

3D image data in the form of computed tomography (CT) and cone beam CT (CBCT) scans of patients receiving external beam radiotheray for bladder cancer were obtained from Edinburgh Cancer Centre (n=132) and used as the input data.

The time taken to process each image volume and each slice of each image volume was recorded for each of the three implementations.

See README file for further details.
Date made available10 Aug 2019
PublisherUniversity of Strathclyde
Date of data production19 Sep 2018 - 10 Aug 2019

Cite this

Robinson, F. (Creator), Crockett, L. H. (Contributor), Stewart, R. (Contributor), Nailon, W. H. (Contributor), McLaren, D. (Contributor). (10 Aug 2019). Performance of Hardware Accelerated Bone Segmentation. University of Strathclyde. README(.txt), hls(.zip), input_data(.zip), ip(.zip), ip_src(.zip), results(.zip), sw(.zip), vivado(.zip). 10.15129/1a667dbc-8202-443d-a52b-45b5f8b498d2