Dr. Kent M. Ogden Profile

Dr. Kent M. Ogden

Assistant Professor at SUNY Upstate Medical Univ

SPIE Involvement:

Author

Publications (29)

Proceedings Article | 12 March 2014 Paper

Dimensional accuracy of 3D printed vertebra

Kent Ogden, Nathaniel Ordway, Dalanda Diallo, Gwen Tillapaugh-Fay, Can Aslan

Proceedings Volume 9036, 903629 (2014) https://doi.org/10.1117/12.2043489

KEYWORDS: 3D metrology, 3D image processing, 3D modeling, 3D printing, Image segmentation, Tissues, Surgery, Computed tomography, Printing, Spine

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Proceedings Article | 11 March 2014 Paper

Comparison of two indirect detection flat panel imagers

Kent Ogden, Kimball Clark, Andrij Wojtowycz, Michele Lisi, Ernest Scalzetti

Proceedings Volume 9037, 90371R (2014) https://doi.org/10.1117/12.2043299

KEYWORDS: Sensors, Image quality, Imaging systems, Image resolution, Image sensors, Medical imaging, Composites, Statistical analysis, Manufacturing, Image compression

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Proceedings Article | 22 February 2012 Paper

Effect of lesion blurring on observer performance in AFC experiments using chest CT images

Kent Ogden, Danielle Williams, Dalanda Jalloh, Marsha Roskopf

Proceedings Volume 8318, 83181B (2012) https://doi.org/10.1117/12.911449

KEYWORDS: Computed tomography, Bone, Chest, Reconstruction algorithms, Lung, Scanners, Medical imaging, Image processing, Physics, Ions

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Proceedings Article | 23 March 2010 Paper

Search field size and lesion detection performance

Sameer Tipnis, Walter Huda, Andrew Hardie, Kent Ogden

Proceedings Volume 7622, 76224U (2010) https://doi.org/10.1117/12.843596

KEYWORDS: Liver, Abdomen, Computed tomography, X-ray computed tomography, Tissues, X-ray imaging, X-rays, Optical spheres, Radiology, Medical imaging

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In this study, we evaluated the ability of an observer to identify abnormal foci on CT and how that ability is affected by changing the search field size from a whole abdomen to the liver region alone. A 2-Alternate Forced Choice (2 AFC) experimental paradigm was used to quantify observer detection performance. Each AFC experiment yielded the intensity needed to achieve 92% accuracy in lesion detection (I92%). Abdominal images were obtained at an x-ray tube voltage of 120 kV with a CTDIvol of 20 mGy. Circular lesions were generated by projecting spheres onto the image plane, followed by blurring function. Five lesion sizes (5 mm, 7 mm, 10 mm, 12 mm, and 15 mm), and four readers who were extensively trained in AFC methodology, were used in the 2AFC experiments. Each experiment was repeated 4 times to improve the experimental precision, as well as to provide an estimate of experimental uncertainty. For each observer, the experimental order of the 40 experiments was randomized to eliminate learning curve and/or observer fatigue. We measured contrast detail slopes for both Abdomen and Liver search field size, and determined ratio of I92% value for Abdomen search field to the corresponding I92% for the Liver search field (i.e., R_abd:liv). Values of Rabd:liv provides quantitative indicator of the relative difficulty of detection lesions in the whole Abdomen relative to lesion detection restricted to the Liver. The slope of the contrast detail curve for the Abdomen search field was -0.03, whereas the corresponding slope for the Liver search field was -0.18. R_abd:liv ranged between 1.3 and 1.6, with an average of 1.4 ± 0.1. The value of Rabd:liv monotonically increased from 1.35 for 5 mm lesions to nearly 1.6 for the largest 15 mm lesion. The results of our study indicate that limiting the area of search to the liver on a CT of the abdomen improves the detection of mass lesions. This finding is almost certainly related to the fact that the liver provides a relatively homogenous background for identifying abnormalities, while the rest of the abdomen is much more heterogeneous. The clinical relevance of our findings is that CT can have limitations for detection of mass lesions outside of the liver, and sizes of masses necessary for detection are larger outside the liver than within.

Proceedings Article | 23 March 2010 Paper

Dose reduction and lesion delectability in abdominal CT

Sameer Tipnis, Walter Huda, Andrew Hardie, Kent Ogden

Proceedings Volume 7622, 76222Q (2010) https://doi.org/10.1117/12.843600

KEYWORDS: X-rays, X-ray computed tomography, Liver, X-ray imaging, Head, Abdomen, Optical simulations, Imaging systems, Diagnostics, X-ray detectors

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Proceedings Article | 24 February 2010 Paper

Effect of background detail on CD curve slope in CT head images

Kent Ogden, Walter Huda, Sameer Tipnis, Marsha Roskopf

Proceedings Volume 7627, 76271A (2010) https://doi.org/10.1117/12.844425

KEYWORDS: Computed tomography, Head, Critical dimension metrology, Diagnostics, CT reconstruction, Image quality, Scanners, Brain, Liver, Performance modeling

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Proceedings Article | 14 March 2009 Paper

The effect of dose reductions on lesion detection in head CT

Saeed Elojeimy, Walter Huda, Kent Ogden, Ryan Owen, Ehsan Samei, Zoran Rumboldt

Proceedings Volume 7258, 72584Q (2009) https://doi.org/10.1117/12.812051

KEYWORDS: X-ray computed tomography, Head, X-rays, Radiation effects, X-ray imaging, Brain, Basal ganglia, Radiology, Imaging systems, Computed tomography

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Proceedings Article | 13 March 2009 Paper

Contrast detail curves in head CT examinations

Saeed Elojeimy, Walter Huda, Kent Ogden, Ryan Owen, Ehsan Samei, Zoran Rumboldt

Proceedings Volume 7263, 726313 (2009) https://doi.org/10.1117/12.811660

KEYWORDS: Computed tomography, Head, Neck, Tissues, X-ray computed tomography, Basal ganglia, Brain, Radiology, X-ray imaging, X-rays

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Proceedings Article | 25 March 2008 Paper

A comparison of three CT voltage optimization strategies

Kent Ogden, Walter Huda, Mohammad Khorasani, Ernest Scalzetti

Proceedings Volume 6913, 691351 (2008) https://doi.org/10.1117/12.773305

KEYWORDS: X-rays, Tissues, Image quality, Lung, X-ray imaging, X-ray computed tomography, Chest, Diagnostics, Imaging systems, Signal attenuation

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Proceedings Article | 6 March 2008 Paper

Inter-reader variability in alternate forced choice studies

W. Huda, K. Ogden, E. Samei, E. Scalzetti, R. Lavallee, M. Roskopf

Proceedings Volume 6917, 691711 (2008) https://doi.org/10.1117/12.770618

KEYWORDS: Computed tomography, Radiology, Data modeling, Abdomen, Diagnostics, Scanners, Medical imaging, CT reconstruction, Solids, X-ray imaging

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Proceedings Article | 6 March 2008 Paper

Reconstruction filters and contrast detail curves in CT

W. Huda, K. Ogden, E. Samei, E. Scalzetti, R. Lavallee, M. Roskopf, G. Groat

Proceedings Volume 6917, 691710 (2008) https://doi.org/10.1117/12.770530

KEYWORDS: Image filtering, Tissues, Bone, CT reconstruction, X-ray computed tomography, Signal to noise ratio, Computed tomography, Scanners, Performance modeling, Optical filters

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Proceedings Article | 19 March 2007 Paper

How do kV and mAs affect CT lesion detection performance?

W. Huda, K. Ogden, K. Shah, C. Jadoo, E. Scalzetti, R. Lavallee, M. Roskopf

Proceedings Volume 6510, 65104P (2007) https://doi.org/10.1117/12.708498

KEYWORDS: X-rays, X-ray computed tomography, X-ray imaging, Image quality, Performance modeling, Signal to noise ratio, Scanners, CT reconstruction, Tissues, X-ray detectors

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Proceedings Article | 8 March 2007 Paper

A method for analyzing contrast-detail curves

K. Ogden, W. Huda, K. Shah, E. Scalzetti, R. Lavallee, M. Roskopf

Proceedings Volume 6515, 65151H (2007) https://doi.org/10.1117/12.708483

KEYWORDS: Critical dimension metrology, Data acquisition, Data modeling, Computed tomography, Software development, Error analysis, Pathology, Image quality, Signal to noise ratio, Diagnostics

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Proceedings Article | 17 March 2006 Paper

How does mass lesion detection vary with display window width and radiation exposure in computed radiography?

K. Ogden, W. Huda, V. Garg, M. Khan, M. Reichel, M. Roskopf

Proceedings Volume 6146, 614611 (2006) https://doi.org/10.1117/12.650735

KEYWORDS: Radiography, Chromium, Visibility, Image processing, Performance modeling, Optical spheres, Target detection, Sensors, X-ray imaging, X-rays

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Proceedings Article | 17 March 2006 Paper

Incorporating detection tasks into the assessment of CT image quality

E. Scalzetti, W. Huda, K. Ogden, M. Khan, M. Roskopf, D. Ogden

Proceedings Volume 6146, 61460F (2006) https://doi.org/10.1117/12.650746

KEYWORDS: Image quality, Computed tomography, Lung, Liver, Diagnostics, X-ray computed tomography, Chest, Image quality standards, Opacity, Lymphatic system

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Proceedings Article | 2 March 2006 Paper

X-ray tube voltage and image quality in adult and pediatric CT

W. Huda, K. M. Ogden, E. M. Scalzetti, R. L. Lavallee, E. Samei

Proceedings Volume 6142, 61422M (2006) https://doi.org/10.1117/12.649279

KEYWORDS: Tissues, Signal to noise ratio, X-rays, Signal attenuation, Bone, X-ray computed tomography, Lung, Image quality, Head, Abdomen

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Proceedings Article | 20 April 2005 Paper

Use of energy imparted as an optimization tool in CT

Ari Jonisch, Walter Huda, Kent Ogden

Proceedings Volume 5745, (2005) https://doi.org/10.1117/12.595607

KEYWORDS: X-ray computed tomography, Head, Scanners, X-rays, Copper, Computed tomography, Aluminum, Neck, Monte Carlo methods, Abdomen

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Proceedings Article | 15 April 2005 Paper

Quantifying the effect of monitor display settings on observer performance

Kent Ogden, Adam Oberlander, Walter Huda, Marsha Roskopf

Proceedings Volume 5748, (2005) https://doi.org/10.1117/12.594626

KEYWORDS: Image display, Digital imaging, Calibration, Standards development, Mammography, Breast, Medical imaging, Data acquisition, Visualization, Transform theory

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Proceedings Article | 6 April 2005 Paper

Contrast-detail curves in chest radiography

Kent Ogden, Ernest Scalzetti, Walter Huda, Jasjeet Saluja, Robert Lavallee

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.595578

KEYWORDS: Radiography, Chest, Lung, Chest imaging, Data modeling, Lung cancer, Pathology, Performance modeling, Image processing, Visualization

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Proceedings Article | 6 May 2004 Paper

Optimizing abdominal CT dose and image quality with respect to x-ray tube voltage

Walter Huda, Kent Ogden

Proceedings Volume 5368, (2004) https://doi.org/10.1117/12.535608

KEYWORDS: X-rays, X-ray computed tomography, X-ray imaging, Iodine, Bone, Image quality, Range imaging, X-ray detectors, Scanners, Diagnostics

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The objective of this study was to identify the x-ray tube voltage that results in optimum performance for abdominal CT imaging for a range of imaging tasks and patient sizes. Theoretical calculations were performed of the contrast to noise ratio (CNR) for disk shaped lesions of muscle, fat, bone and iodine embedded in a uniform water background. Lesion contrast was the mean Hounsfield Unit value at the effective photon energy, and image noise was determined from the total radiation intensity incident on the CT x-ray detector. Patient size ranging from young infants (10 kg) to oversized adults (120 kg), with CNR values obtained for x-ray tube voltages ranging from 80 to 140 kV. Patients of varying sizes were modeled as an equivalent cylinder of water, and the mean section dose (D) was determined for each selected x-ray tube kV value at a constant mAs. For each patient size and lesion type, we identified an optimal kV as the x-ray tube voltage that yields a maximum value of the figure of merit (CNR2/D). Increasing the x-ray tube voltage from 80 to 140 kV reduced lesion contrast by 11% for muscle, 21% for fat, 35% for bone and 52% for iodine, and these reductions were approximately independent of patient size. Increasing the x-ray tube voltage from 80 to 140 kV increased a muscle lesion CNR relative to a uniform water background by a factor of 2.6, with similar trends observed for fat (2.3), bone (1.9) and iodine (1.4). The improvement in lesion CNR with increasing x-ray tube voltage was highest for the largest sized patients. Increasing the x-ray tube voltage from 80 to 140 kV increased the patient dose by a factor of between 5.0 and 6.2 depending on the patient size. For small sized patients (10 and 30 kg) and muscle lesions, best performance is obtained at 80 kV; however, for adults (70 kg) and oversized adults (120 kg), the best performance would be obtained at 140 kV. Imaging fat lesions was best performed at 80 kV for all patients except for oversized adults, where 140 kV offers the best imaging performance. For high Z lesions of bone and iodine, imaging performance generally degrades with increasing kV for all patient sizes, with the degree of degradation largest for the smallest patients. We conclude that 80 kV is optimal with respect to radiation dose in abdominal CT for all pediatric patients. For adults, 80 kV is the x-ray voltage of choice for high Z lesions, whereas 140 kV would generally be the voltage of choice of lesions that have an atomic number similar to that of water.

Proceedings Article | 4 May 2004 Paper

How do radiographic techniques affect mass lesion detection performance in digital mammography?

Walter Huda, Kent Ogden, Ernest Scalzetti, Eric Dudley, David Dance

Proceedings Volume 5372, (2004) https://doi.org/10.1117/12.535672

KEYWORDS: X-rays, Digital mammography, Image quality, Digital imaging, Mammography, Breast, Solids, Performance modeling, X-ray imaging, Visibility

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Proceedings Article | 4 May 2004 Paper

How does the concentration of iodine in enhancing lesions relate to image quality in head CT?

Aaron Fischman, Robert Dixon, Walter Huda, Kent Ogden, Kristin Lieberman, Marsha Roskopf

Proceedings Volume 5372, (2004) https://doi.org/10.1117/12.535645

KEYWORDS: Iodine, Image enhancement, Computed tomography, Head, Signal to noise ratio, Image quality, Image processing, Receivers, Diagnostics, Tumors

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Patients undergoing head CT examinations with iodinated contrast received 100 cc of Iohexol 240 injected intravenously by hand. We developed a software package to align non-contrast and contrast head CT images, and obtain the “difference image” consisting of the iodine enhancement within a given lesion. This “difference image” of the iodine enhancement was added to the non-contrast study at reduced intensities. The signal to noise ratio (SNR) for detecting the added iodine was taken to be directly proportional to the concentration of contrast in the lesion. The visibility of the lesion enhancement in this composite image was compared with the original contrast image using a six-point scale ranging from 5 (no observable difference) to 0 (unacceptable). Two radiologists evaluated head CT images of eleven metastatic lesions. The iodine concentration required to generate an image quality rank of 3, deemed to be satisfactory for diagnosis (S), was determined. We also performed a Receiver Operating Characteristic (ROC) study to identify the iodine concentration corresponding to an area under the ROC curve of 0.95, which corresponds to the detection threshold (D) for each lesion. Reducing the intensity to 50% resulted in an average image qualtiy score S of 3, suggesting that it may be possible to reduce the administered iodine by a half in head CT examinations with no significant loss of diagnostic performance. The average iodine concentration at the detection threshold D was 16%. The average S:D ratio was 3.8 ± 1.7, and was similar for both readers. The value of S was independent of enhancement characteristics, whereas the detection threshold D correlated inversely with the size and intensity of the iodine enhancement. The resultant S:D ratio correlated with the lesion area (r² = 0.31), mean lesion intensity (r² = 0.44), and the product of the mean lesion intensity and the lesion area (r² = 0.37). Our results indicate that the SNR of enhancing lesions in head CT that is needed to satisfy radiologists is about a factor of four greater than the SNR required for iodine detection.

Proceedings Article | 5 June 2003 Paper

General approach to optimizing digital mammography with respect to radiation risk

Kent Ogden, Walter Huda, Ernest Scalzetti

Proceedings Volume 5030, (2003) https://doi.org/10.1117/12.479972

KEYWORDS: X-rays, Image quality, Digital mammography, Imaging systems, X-ray imaging, Radiology, Breast cancer, Diagnostics, Radiography, Mammography

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Proceedings Article | 22 May 2003 Paper

How does lesion location affect detection performance in digital mammography?

Walter Huda, Kent Ogden, Ernest Scalzetti, Joon Park, Roger Hunt, David Dance

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480085

KEYWORDS: Mammography, Breast, Digital mammography, Signal detection, Convolution, Digital imaging, Radiography, Visibility, X-rays, Solids

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Proceedings Article | 9 May 2002 Paper

Contrast improvements in digital radiography using a scatter-reduction processing algorithm

Kent Ogden, Charles Wilson, Robert Cox

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467059

KEYWORDS: Expectation maximization algorithms, Image processing, Algorithm development, Point spread functions, Radiography, X-rays, Signal attenuation, Sensors, Chest, Scatter measurement

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Proceedings Article | 3 May 2002 Paper

Optimizing the x-ray photon energy for digital radiographic imaging systems

Walter Huda, Harry Kissi, Kent Ogden, John Boone

Proceedings Volume 4682, (2002) https://doi.org/10.1117/12.465608

KEYWORDS: X-rays, X-ray imaging, Iodine, Calcium, Image quality, Quantum efficiency, Imaging systems, X-ray detectors, Radiography, Tissues

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Proceedings Article | 12 April 2002 Paper

Observer performance and radiographic technique factors in digital mammography

Anthony Sajewicz, Walter Huda, Denis Hseuh, Kent Ogden, Ernest Scalzetti, David Dance

Proceedings Volume 4686, (2002) https://doi.org/10.1117/12.462668

KEYWORDS: Visibility, Digital mammography, Mammography, X-rays, Medical imaging, Digital imaging, Breast, X-ray imaging, Imaging systems, Image sensors

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Proceedings Article | 28 June 2001 Paper

Comparison of the imaging physics performance of a prototype flat-panel detector with a 400-speed screen-film system

Walter Huda, Kent Ogden, Marsha Roskopf, Charles Rush

Proceedings Volume 4320, (2001) https://doi.org/10.1117/12.430954

KEYWORDS: Sensors, Imaging systems, Digital imaging, Physics, X-rays, Spatial resolution, Image processing, Image resolution, Prototyping, Digital image processing

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Proceedings Article | 28 May 2001 Paper

Optimizing softcopy display of radiographic images acquired with a prototype flat-panel detector

Walter Huda, Kent Ogden, Ernest Scalzetti, Mahmoud El-kaissi

Proceedings Volume 4319, (2001) https://doi.org/10.1117/12.428091

KEYWORDS: Image quality, Sensors, Image processing, Prototyping, Radiography, Chest, Flat panel displays, Skull, Neck, X-ray detectors

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Showing 5 of 29 publications

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