Dr. Wouter J. H. Veldkamp Profile

Dr. Wouter J. H. Veldkamp

at Leids Univ Medisch Ctr

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Publications (8)

SPIE Journal Paper | 26 June 2023 Open Access

Lesion detection in digital breast tomosynthesis: human reader experiments indicate no benefit from the integration of information from multiple planes

Christiana Balta, Ingrid Reiser, Mireille J. M. Broeders, Wouter J. H. Veldkamp, Ruben E. van Engen, Ioannis Sechopoulos

JMI, Vol. 10, Issue S1, S11915, (June 2023) https://doi.org/10.1117/12.10.1117/1.JMI.10.S1.S11915

KEYWORDS: Digital breast tomosynthesis, 3D image processing, Breast, Optical spheres, 3D acquisition, Spherical lenses, Signal detection, 3D vision, Target detection, Computed tomography

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PurposeIn digital breast tomosynthesis (DBT), radiologists need to review a stack of 20 to 80 tomosynthesis images, depending upon breast size. This causes a significant increase in reading time. However, it is currently unknown whether there is a perceptual benefit to viewing a mass in the 3D tomosynthesis volume. To answer this question, this study investigated whether adjacent lesion-containing planes provide additional information that aids lesion detection for DBT-like and breast CT-like (bCT) images.MethodHuman reader detection performance was determined for low-contrast targets shown in a single tomosynthesis image at the center of the target (2D) or shown in the entire tomosynthesis image stack (3D). Using simulations, targets embedded in simulated breast backgrounds, and images were generated using a DBT-like (50 deg angular range) and a bCT-like (180 deg angular range) imaging geometry. Experiments were conducted with spherical and capsule-shaped targets. Eleven readers reviewed 1600 images in two-alternative forced-choice experiments. The area under the receiver operating characteristic curve (AUC) and reading time were computed for the 2D and 3D reading modes for the DBT and bCT imaging geometries and for both target shapes.ResultsSpherical lesion detection was higher in 2D mode than in 3D, for both DBT- and bCT-like images (DBT: AUC2D = 0.790, AUC3D = 0.735, P = 0.03; bCT: AUC2D = 0.869, AUC3D = 0.716, P < 0.05), but equivalent for capsule-shaped signals (DBT: AUC2D = 0.891, AUC3D = 0.915, P = 0.19; bCT: AUC2D = 0.854, AUC3D = 0.847, P = 0.88). Average reading time was up to 134% higher for 3D viewing (P < 0.05).ConclusionsFor the detection of low-contrast lesions, there is no inherent visual perception benefit to reviewing the entire DBT or bCT stack. The findings of this study could have implications for the development of 2D synthetic mammograms: a single synthesized 2D image designed to include all lesions present in the volume might allow readers to maintain detection performance at a significantly reduced reading time.

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SPIE Journal Paper | 27 September 2019

Optimization of the difference-of-Gaussian channel sets for the channelized Hotelling observer

Christiana Balta, Ramona Bouwman, Mireille J. Broeders, Nico Karssemeijer, Wouter J. Veldkamp, Ioannis Sechopoulos, Ruben van Engen

JMI, Vol. 6, Issue 03, 035501, (September 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.3.035501

KEYWORDS: Signal detection, Image quality, Breast, Image processing, Image analysis, Medical imaging, Digital mammography, Digital image processing, Gold, Radiology

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Proceedings Article | 4 March 2019 Presentation + Paper

2D single-slice vs. 3D viewing of simulated tomosynthesis images of a small-scale breast tissue model

Christiana Balta, Ioannis Sechopoulos, Wouter J. Veldkamp, Ruben van Engen, Ingrid Reiser

Proceedings Volume 10952, 109520V (2019) https://doi.org/10.1117/12.2512053

KEYWORDS: Breast, 3D image processing, Signal detection, 3D modeling, Tissues, Image quality, 3D vision, 3D displays, Computer simulations, Spherical lenses

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Proceedings Article | 4 March 2019 Presentation + Paper

New difference of Gaussian channel-sets for the channelized Hotelling observer?

Christiana Balta, Ioannis Sechopoulos, Ramona Bouwman, Mireille J. Broeders, Nico Karssemeijer, Ruben van Engen, Wouter J. Veldkamp

Proceedings Volume 10952, 109520C (2019) https://doi.org/10.1117/12.2512054

KEYWORDS: Signal detection, Breast, Image quality, Gold, Radiology, Digital mammography, Digital imaging, Aluminum, Nuclear medicine, Mammography

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SPIE Journal Paper | 8 September 2018

Signal template generation from acquired images for model observer-based image quality analysis in mammography

Christiana Balta, Ramona W. Bouwman, Wouter J. H. Veldkamp, Mireille J. M. Broeders, Ioannis Sechopoulos, Ruben E. van Engen

JMI, Vol. 5, Issue 03, 035503, (September 2018) https://doi.org/10.1117/12.10.1117/1.JMI.5.3.035503

KEYWORDS: Image processing, Molybdenum, Breast, Gold, Signal generators, Image quality, Mammography, Signal detection, Image analysis, Signal processing

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Proceedings Article | 10 March 2017 Presentation + Paper

Signal template generation from acquired mammographic images for the non-prewhitening model observer with eye-filter

Christiana Balta, Ramona Bouwman, Ioannis Sechopoulos, Mireille J. M. Broeders, Nico Karssemeijer, Ruben van Engen, Wouter J. H. Veldkamp

Proceedings Volume 10136, 101360M (2017) https://doi.org/10.1117/12.2254160

KEYWORDS: Eye models, Breast, Image quality, Image filtering, Digital mammography, Signal detection, Aluminum, Gold

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Proceedings Article | 17 March 2015 Paper

Evaluation of six channelized Hotelling observers in combination with a contrast sensitivity function to predict human observer performance

Marco Goffi, Wouter J. Veldkamp, Ruben van Engen, Ramona Bouwman

Proceedings Volume 9416, 94160Z (2015) https://doi.org/10.1117/12.2081528

KEYWORDS: Image quality, Contrast sensitivity, Statistical analysis, Image analysis, Image filtering, Eye models, Interference (communication), Systems modeling, Medical imaging, Digital mammography

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Proceedings Article | 21 May 1999 Paper

Improved method for detection of microcalcification clusters in digital mammograms

Wouter Veldkamp, Nico Karssemeijer

Proceedings Volume 3661, (1999) https://doi.org/10.1117/12.348607

KEYWORDS: Mammography, Feature selection, Image segmentation, Feature extraction, Breast, Mahalanobis distance, Image processing, Distance measurement, Statistical methods, Databases

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