Multimodal Breast Cancer Imaging Using Coregistered Dynamic DOT and Digital Breast Tomosynthesis

Deng, Bin; Zimmermann, Bernhard; Singh, Bhawana; Fang, Qianqian; Cormier, Jayne; Moore, Richard H.; Kopans, Daniel B.; Saksena, Mansi; Boas, David A.; Carp, Stefan A.

doi:10.1364/ots.2018.of4d.4

Cited by 1 publication

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“…Equation (11) includes the imaging models of all X-ray sources in every snapshot. However, in each snapshot only one X-ray source is allowed to be turned on.…”

Section: Dynamic Tomosynthesis Imaging Modelmentioning

confidence: 99%

“…X-ray tomosynthesis to date has been used increasingly in non-destructive material testing, industrial flaw detection, security inspection, as well as human medical diagnosis [1]- [11].Tomosynthesis systems interrogate three-dimensional (3D) objects under inspection from cone beam measurements coming from a few incident directions. Given a set of two-dimensional (2D) projection measurements on the area detector, the internal structure and components of the 3D object can be reconstructed from the 2D projection measurements based on computer-processed algorithms [1], [2], [12]- [18].Compared to conventional X-ray computed tomography (CT) that requires a full set of measurements around the object, tomosynthesis approaches can effectively reduce the radiation dose, acquisition time and geometrical complexity of the systems since only a reduced set of measurements from limited view angles are needed [19]- [23].…”

Section: Introductionmentioning

confidence: 99%

“…This is a lead. In recent years, digital breast tomosynthesis provides images with high spatial resolution at a dose comparable to a 2D digital mammogram and have very high spatial resolution [10], [11]. It is foreseeable that low-dose imaging will be a prevalent development trend in X-ray tomosynthesis systems as tomosynthesis is becoming increasingly common for all kinds of diagnosis tasks.…”

Section: Introductionmentioning

confidence: 99%

“…The aforementioned compressive tomosynthesis methods, however, are confined to the static modality, where the object is assumed to be stationary during the entire measurement procedure. In some medical application scenarios such as full body scans or batch testing of biological samples [2], [6]- [11], objects of interest move forward continuously on the conveyor, which results in the variations of the sensing geometry. The object herein refers to the human body or other biological samples under detection.…”

Section: Introductionmentioning

confidence: 99%

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Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination

Wang

Cuadros

et al. 2020

IEEE Photonics J.

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Compressive X-ray tomosynthesis is a computational imaging technique used to reconstruct three-dimensional objects from a set of projection measurements, where the masks are used to modulate the structured illumination to reduce the radiation dose while retaining the reconstruction performance. This paper proposes a conveyor X-ray tomosynthesis imaging method with optimized structured sequential illumination. Variations of this geometry where the object is static but the measurement gantry is dynamic are possible within the proposed framework. In this system, several X-ray sources are successively used to interrogate the moving object lying on a conveyor, where the compressive measurements are received by a set of low-cost strip detectors. The dynamic imaging model and reconstruction framework of the proposed system are established taking into account sensing geometry along with the movement of the object. Subsequently, a genetic algorithm is developed to optimize the exposure sequence of X-ray sources and mask patterns and during the dynamic measurement process. The optimization problem is formulated based on the restricted isometry property of compressive sensing theory to ameliorate the ill-posed inverse tomosynthesis problem. The optimized structured sequential illumination is proved to significantly improve the imaging performance of the conveyor X-ray tomosynthesis system based on a set of simulations.

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“…Equation (11) includes the imaging models of all X-ray sources in every snapshot. However, in each snapshot only one X-ray source is allowed to be turned on.…”

Section: Dynamic Tomosynthesis Imaging Modelmentioning

confidence: 99%