Image processing

Image quality evaluation, assessment, and modification are important factors in medical imaging, since a change in image quality could potentially modify the clinical performance of radiologists or of automated image analysis algorithms. Although image quality is primary defined by the physical characteristics of a medical imaging system, processing algorithms can be developed to maximize the image quality in post-acquisition phases. Within our research group, we are developing image denoising and scatter correction models to maximize image quality in x-ray-based imaging, and we are designing frameworks and systems to predict the clinical performance of imaging technologies for detection and diagnosis tasks.


Projects

Optimization and assessment of digital breast tomosynthesis
Optimization and assessment of digital breast tomosynthesis Digital breast tomosynthesis is undergoing a continuous evolution, with special focus in new acquisition protocols that can enhance its clinical performance, reduce radiation dose to the patients and improve reading workflow, More...
Optimizing quality control procedures in Digital Mammography and Digital Breast Tomosynthesis
Optimizing quality control procedures in Digital Mammography and Digital Breast Tomosynthesis Assessment of clinical image quality can be performed with human observers, such as medical physicists and radiologists, and with images of anthropomorphic phantoms or with clinical images. More...
Image quality evaluation test for clinical performance prediction in digital mammography
Image quality evaluation test for clinical performance prediction in digital mammography Image quality evaluation in mammographic screening is an important factor for optimizing the early detection of breast cancer. More...
Breast Shape Models
Breast Shape Models Many applications in breast imaging such as dosimetry models, x-ray scatter correction algorithms, and image processing techniques require realistic virtual breast models. We aim to provide objective models for use with these methods. More...
Image denoising and scatter modelling and correction
Image denoising and scatter modelling and correction In x-ray imaging, several factors can negatively affect the image quality and potentially hide an abnormality, first among all the image noise produced by the random photon distribution within the image, and the x-rays scattering. More...