Prof. Hilde Bosmans
Group Manager Medical Physics at UZ Leuven
SPIE Involvement:
Conference Chair | Editor | Author | Instructor
Publications (79)

Proceedings Article | 22 May 2020
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Medicine, Visualization, Mammography, Digital mammography, Digital breast tomosynthesis

Proceedings Article | 22 May 2020
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Statistical analysis, Breast cancer, Tumors, Visualization, Tissues, Image segmentation, Pathology, Mammography, Digital breast tomosynthesis

Proceedings Article | 22 May 2020
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Visualization, Imaging systems, Scanners, Image analysis, Image quality, Digital breast tomosynthesis

Proceedings Article | 22 May 2020
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Target detection, Image quality, Image quality standards, Digital breast tomosynthesis

Proceedings Article | 22 May 2020
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Polymethylmethacrylate, Visualization, Sensors, Calibration, Image processing, Collimators, Mammography, Medical physics, Digital mammography

Showing 5 of 79 publications
Proceedings Volume Editor (3)

SPIE Conference Volume | 29 May 2020

SPIE Conference Volume | 22 May 2020

SPIE Conference Volume | 9 July 2019

Conference Committee Involvement (12)
Physics of Medical Imaging
14 February 2021 | San Diego, California, United States
Fifteenth International Workshop on Breast Imaging
24 May 2020 | Leuven, Belgium
Physics of Medical Imaging
16 February 2020 | Houston, Texas, United States
Physics of Medical Imaging
17 February 2019 | San Diego, California, United States
Physics of Medical Imaging
12 February 2018 | Houston, Texas, United States
Showing 5 of 12 Conference Committees
Course Instructor
SC1292: Technological Assessment of X-Ray Based Breast Imaging Systems Using Anthropomorphic Phantoms
Development of new breast X-ray imaging technologies or improvements to hardware or software of current systems usually require the accurate assessment of image quality. Image quality assessment methods are also required for quality control (QC) of clinical systems, for example as required by the U.S. Mammography Quality Standards Act (MQSA) program. The gold standard for assessment of image quality is human reader studies assessing diagnostic performance over a cohort of representative clinical images. These clinical trials are often difficult and expensive to perform, and therefore researchers have been studying alternative approaches that can assess diagnostic task performance without imaging patients. This short course will discuss methods for objectively assessing task performance of breast imaging systems without conducting a clinical trial. One approach that will be discussed is the in silico modeling of a clinical trial. This approach involves complete computer modeling of each step in the imaging chain including: 1) modeling of breast and relevant breast lesions, 2) modeling of the imaging system, and 3) modeling of the observer. Another more experimental approach that will also be discussed involves: 1) development of anthropomorphic physical phantoms with diagnostic features, 2) imaging of these phantoms on breast imaging commercial or prototype systems, and 3) assessment of task performance with either model or human observers. For maximum efficiency, the proposed in silico and experimental approaches require the development of computer or model observers that can emulate either ideal or human observer task performance. This short course will discuss the use of new machine learning algorithms that can be used to model observer performance in the assessment of breast imaging technology. This course will describe and make attendees aware of useful open-source software tools that can be downloaded.
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