Abstract
| Language | English |
|---|---|
| Number of pages | 1 |
| Publication status | Published - 23 Jun 2017 |
| Event | Centre for Doctoral Training in Applied Photonics Annual Conference 2017 - Heriot-Watt University, Edinburgh, United Kingdom Duration: 23 Jun 2017 → 23 Jun 2017 |
Conference
| Conference | Centre for Doctoral Training in Applied Photonics Annual Conference 2017 |
|---|---|
| Country | United Kingdom |
| City | Edinburgh |
| Period | 23/06/17 → 23/06/17 |
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Keywords
- image processing
- biomedical imaging
- tomographic imaging
- image registration
Cite this
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Correlation of pre-operative cancer imaging techniques with post-operative gross and microscopic pathologic images. / Reines March, G.; Ju, X.; Marshall, S.
2017. Poster session presented at Centre for Doctoral Training in Applied Photonics Annual Conference 2017, Edinburgh, United Kingdom.Research output: Contribution to conference › Poster
TY - CONF
T1 - Correlation of pre-operative cancer imaging techniques with post-operative gross and microscopic pathologic images
AU - Reines March, G.
AU - Ju, X.
AU - Marshall, S.
PY - 2017/6/23
Y1 - 2017/6/23
N2 - During this first year, different algorithms for volume reconstruction from tomographic slices have been tested. A tissue-mimicking phantom made with a mixture of agar and aluminium oxide was sliced at different thicknesses as per pathological standard guidelines. Phantom model was also virtually sliced and reconstructed in software. Results showed that shape-based spline interpolation method was the most precise, but generated a volume underestimation of 0.5%. Nearest neighbour interpolation produced the most accurate values.
AB - During this first year, different algorithms for volume reconstruction from tomographic slices have been tested. A tissue-mimicking phantom made with a mixture of agar and aluminium oxide was sliced at different thicknesses as per pathological standard guidelines. Phantom model was also virtually sliced and reconstructed in software. Results showed that shape-based spline interpolation method was the most precise, but generated a volume underestimation of 0.5%. Nearest neighbour interpolation produced the most accurate values.
KW - image processing
KW - biomedical imaging
KW - tomographic imaging
KW - image registration
UR - https://www.cdtphotonics.hw.ac.uk/
M3 - Poster
ER -