TY  - JOUR
  - McWilliams, S. R.,O'Connor, O. J.,McGarrigle, A. M.,O'Neill, S. B.,Quigley, E. M.,Shanahan, F.,Maher, M. M.
  - 2012
  - June
  - Journal of Medical Imaging and Radiation Oncology
  - CT-based estimation of intracavitary gas volumes using threshold-based segmentation: in vitro study to determine the optimal threshold range
  - Validated
  - ()
  - 56
  - 33
  - 289
  - 294
  - INTRODUCTION: This study investigated the optimal Hounsfield unit (HU) threshold range when using threshold-based segmentation to estimate volumes of contained gas (i.e. intestinal gas) on CT. METHODS: A water-filled cylindrical acrylic imaging phantom containing two saline bags modified to allow injection of known volumes of gas (room air) was constructed. The phantom was imaged with CT following injection of known gas volumes. Images were analysed using standard threshold-based 3D region growing with human-entered seed points. The lower threshold was -1024 HU, and upper thresholds between -700 HU and -200 HU were tested for each volume. Appropriate statistical analysis was performed. RESULTS: Measurements were normally distributed. There was excellent correlation between measured and injected volumes for all thresholds (Pearson's r > 0.99). The optimal upper threshold for small gas volumes (1-6 mL) was -550 HU with 0.1% +/- 3.9% (mean +/- standard deviation) error. The optimal upper threshold for large gas volumes (10-50 mL) was -350 HU with 0.7 +/- 3.6% (mean +/- standard deviation) error with Pearson correlations of r > 0.99 for both. CONCLUSION: Accurate estimation of gas volumes on CT is possible using threshold-based segmentation software with a wide range of upper thresholds. The optimal upper threshold for estimation of small volumes (1-6 mL) was -550 HU and -350 HU for volumes of 10-50 mL.INTRODUCTION: This study investigated the optimal Hounsfield unit (HU) threshold range when using threshold-based segmentation to estimate volumes of contained gas (i.e. intestinal gas) on CT. METHODS: A water-filled cylindrical acrylic imaging phantom containing two saline bags modified to allow injection of known volumes of gas (room air) was constructed. The phantom was imaged with CT following injection of known gas volumes. Images were analysed using standard threshold-based 3D region growing with human-entered seed points. The lower threshold was -1024 HU, and upper thresholds between -700 HU and -200 HU were tested for each volume. Appropriate statistical analysis was performed. RESULTS: Measurements were normally distributed. There was excellent correlation between measured and injected volumes for all thresholds (Pearson's r > 0.99). The optimal upper threshold for small gas volumes (1-6 mL) was -550 HU with 0.1% +/- 3.9% (mean +/- standard deviation) error. The optimal upper threshold for large gas volumes (10-50 mL) was -350 HU with 0.7 +/- 3.6% (mean +/- standard deviation) error with Pearson correlations of r > 0.99 for both. CONCLUSION: Accurate estimation of gas volumes on CT is possible using threshold-based segmentation software with a wide range of upper thresholds. The optimal upper threshold for estimation of small volumes (1-6 mL) was -550 HU and -350 HU for volumes of 10-50 mL.
  - 1754-94771754-9477
DA  - 2012/06
ER  - 

@article{V280546647,
   = {McWilliams,  S. R. and O'Connor,  O. J. and McGarrigle,  A. M. and O'Neill,  S. B. and Quigley,  E. M. and Shanahan,  F. and Maher,  M. M. },
   = {2012},
   = {June},
   = {Journal of Medical Imaging and Radiation Oncology},
   = {CT-based estimation of intracavitary gas volumes using threshold-based segmentation: in vitro study to determine the optimal threshold range},
   = {Validated},
   = {()},
   = {56},
   = {33},
  pages = {289--294},
   = {{INTRODUCTION: This study investigated the optimal Hounsfield unit (HU) threshold range when using threshold-based segmentation to estimate volumes of contained gas (i.e. intestinal gas) on CT. METHODS: A water-filled cylindrical acrylic imaging phantom containing two saline bags modified to allow injection of known volumes of gas (room air) was constructed. The phantom was imaged with CT following injection of known gas volumes. Images were analysed using standard threshold-based 3D region growing with human-entered seed points. The lower threshold was -1024 HU, and upper thresholds between -700 HU and -200 HU were tested for each volume. Appropriate statistical analysis was performed. RESULTS: Measurements were normally distributed. There was excellent correlation between measured and injected volumes for all thresholds (Pearson's r > 0.99). The optimal upper threshold for small gas volumes (1-6 mL) was -550 HU with 0.1% +/- 3.9% (mean +/- standard deviation) error. The optimal upper threshold for large gas volumes (10-50 mL) was -350 HU with 0.7 +/- 3.6% (mean +/- standard deviation) error with Pearson correlations of r > 0.99 for both. CONCLUSION: Accurate estimation of gas volumes on CT is possible using threshold-based segmentation software with a wide range of upper thresholds. The optimal upper threshold for estimation of small volumes (1-6 mL) was -550 HU and -350 HU for volumes of 10-50 mL.INTRODUCTION: This study investigated the optimal Hounsfield unit (HU) threshold range when using threshold-based segmentation to estimate volumes of contained gas (i.e. intestinal gas) on CT. METHODS: A water-filled cylindrical acrylic imaging phantom containing two saline bags modified to allow injection of known volumes of gas (room air) was constructed. The phantom was imaged with CT following injection of known gas volumes. Images were analysed using standard threshold-based 3D region growing with human-entered seed points. The lower threshold was -1024 HU, and upper thresholds between -700 HU and -200 HU were tested for each volume. Appropriate statistical analysis was performed. RESULTS: Measurements were normally distributed. There was excellent correlation between measured and injected volumes for all thresholds (Pearson's r > 0.99). The optimal upper threshold for small gas volumes (1-6 mL) was -550 HU with 0.1% +/- 3.9% (mean +/- standard deviation) error. The optimal upper threshold for large gas volumes (10-50 mL) was -350 HU with 0.7 +/- 3.6% (mean +/- standard deviation) error with Pearson correlations of r > 0.99 for both. CONCLUSION: Accurate estimation of gas volumes on CT is possible using threshold-based segmentation software with a wide range of upper thresholds. The optimal upper threshold for estimation of small volumes (1-6 mL) was -550 HU and -350 HU for volumes of 10-50 mL.}},
  issn = {1754-94771754-9477},
  source = {IRIS}
}