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Disambiguation of "Marshall, Nicholas"

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Performance evaluation of a 3D structured phantom with simulated lesions on breast imaging systems.

, , , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 107180Y. SPIE, (2018)

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Michael Marshall

Jonathan Marshall

Ingrid Marshall

Lisa Marshall

Gerd Marshall

 

Other publications of authors with the same name

A European Protocol for Technical Quality Control of Breast Tomosynthesis Systems., , , , , , , , , and 1 other author(s). Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 452-459. Springer, (2014)Towards a Phantom for Multimodality Performance Evaluation of Breast Imaging: A 3D Structured Phantom with Simulated Lesions Tested for 2D Digital Mammography., , , , and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 243-253. Springer, (2016)Anthropomorphic ResNet18 for multi-vendor DBT image quality evaluation., , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 1131616. SPIE, (2020)Development and application of a channelized Hotelling observer for DBT optimization on structured background test images with mass simulating targets., , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 9787 of SPIE Proceedings, page 97871K. SPIE, (2016)Effective Detective Quantum Efficiency (eDQE) Measured for a Digital Breast Tomosynthesis System., , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 127-133. Springer, (2014)The simulation of 3D microcalcification clusters in 2D digital mammography and breast tomosynthesis, , , , , , , , and . Medical Physics, 38 (12): 6659-6671 (2011)Deep learning channelized Hotelling observer for multi-vendor DBT system image quality evaluation., , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160X. SPIE, (2020)First results with a deep learning (feed-forward CNN) approach for daily quality control in digital breast tomosynthesis., , , and . IWBI, volume 10718 of SPIE Proceedings, page 1071819. SPIE, (2018)Performance evaluation of a 3D structured phantom with simulated lesions on breast imaging systems., , , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 107180Y. SPIE, (2018)Model and human observer reproducibility for detecting microcalcifications in digital breast tomosynthesis images., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10577 of SPIE Proceedings, page 105770B. SPIE, (2018)