Modeling the Anisotropic Resolution and Noise Properties of Digital Breast Tomosynthesis

Digital breast tomosynthesis (DBT) is a 3D imaging modality in which a reconstruction of the breast is generated from various x-ray projections. Due to the newness of this technology, the development of an analytical model of image quality has been on-going. In this thesis, a more complete model is developed by addressing the limitations found in the previous linear systems (LS) model [Zhao, Med. Phys. 2008, 35(12): 5219-32]. A central assumption of the LS model is that the angle of x-ray incidence is approximately normal to the detector in each projection. To model the effect of oblique x-ray incidence, this thesis generalizes Swank\u27s calculations of the transfer functions of x-ray fluorescent screens to arbitrary incident angles. In the LS model, it is also assumed that the pixelation in the reconstruction grid is the same as the detector; hence, the highest frequency that can be resolved is the detector alias frequency. This thesis considers reconstruction grids with smaller pixelation to investigate super-resolution, or visibility of higher frequencies. A sine plate is introduced as a conceptual test object to analyze super-resolution. By orienting the long axis of the sine plate at various angles, the feasibility of oblique reconstruction planes is also investigated. This formulation differs from the LS model in which reconstruction planes are parallel to the breast support. It is shown that the transfer functions for arbitrary angles of x-ray incidence can be modeled in closed form. The high frequency modulation transfer function (MTF) and detective quantum efficiency (DQE) are degraded due to oblique x-ray incidence. In addition, using the sine plate, it is demonstrated that a reconstruction can resolve frequencies exceeding the detector alias frequency. Experimental images of bar patterns verified the existence of super-resolution. Anecdotal clinical examples showed that super-resolution improves the visibility of microcalcifications. The feasibility of oblique reconstructions was established theoretically with the sine plate and was validated experimentally with bar patterns. This thesis develops a more complete model of image quality in DBT by addressing the limitations of the LS model. In future studies, this model can be used as a tool for optimizing DBT

System Characterizations and Optimized Reconstruction Methods for Novel X-ray Imaging

In the past decade there have been many new emerging X-ray based imaging technologies developed for different diagnostic purposes or imaging tasks. However, there exist one or more specific problems that prevent them from being effectively or efficiently employed. In this dissertation, four different novel X-ray based imaging technologies are discussed, including propagation-based phase-contrast (PB-XPC) tomosynthesis, differential X-ray phase-contrast tomography (D-XPCT), projection-based dual-energy computed radiography (DECR), and tetrahedron beam computed tomography (TBCT). System characteristics are analyzed or optimized reconstruction methods are proposed for these imaging modalities. In the first part, we investigated the unique properties of propagation-based phase-contrast imaging technique when combined with the X-ray tomosynthesis. Fourier slice theorem implies that the high frequency components collected in the tomosynthesis data can be more reliably reconstructed. It is observed that the fringes or boundary enhancement introduced by the phase-contrast effects can serve as an accurate indicator of the true depth position in the tomosynthesis in-plane image. In the second part, we derived a sub-space framework to reconstruct images from few-view D-XPCT data set. By introducing a proper mask, the high frequency contents of the image can be theoretically preserved in a certain region of interest. A two-step reconstruction strategy is developed to mitigate the risk of subtle structures being oversmoothed when the commonly used total-variation regularization is employed in the conventional iterative framework. In the thirt part, we proposed a practical method to improve the quantitative accuracy of the projection-based dual-energy material decomposition. It is demonstrated that applying a total-projection-length constraint along with the dual-energy measurements can achieve a stabilized numerical solution of the decomposition problem, thus overcoming the disadvantages of the conventional approach that was extremely sensitive to noise corruption. In the final part, we described the modified filtered backprojection and iterative image reconstruction algorithms specifically developed for TBCT. Special parallelization strategies are designed to facilitate the use of GPU computing, showing demonstrated capability of producing high quality reconstructed volumetric images with a super fast computational speed. For all the investigations mentioned above, both simulation and experimental studies have been conducted to demonstrate the feasibility and effectiveness of the proposed methodologies

Endorectal Digital Prostate Tomosynthesis

Several areas of prostate cancer (PCa) management, such as imaging permanent brachytherapy implants or small, aggressive lesions, benefit from high image resolution. Current PCa imaging methods can have inadequate resolution for imaging these areas. Endorectal digital prostate tomosynthesis (endoDPT), an imaging method that combines an external x-ray source and an endorectal x-ray sensor, can produce three-dimensional images of the prostate region that have high image resolution compared to typical methods. This high resolution may improve PCa management and increase positive outcomes in affected men. This dissertation presents the initial development of endoDPT, including system design, image quality assessment, and examples of possible applications to prostate imaging. Experiments using computational phantoms, physical phantoms, and canine prostate specimens were conducted. Initial system design was performed computationally and three methods of endoDPT image reconstruction were developed: shift and add (SAA), backprojection (BP), and filtered BP (FBP). A physical system was developed using an XDR intraoral x-ray sensor and a GE radiography unit. The resolution and radiation dose of endoDPT were measured and compared to a GE CT scanner. Canine prostate specimens that approximated clinical cases of PCa management were imaged and compared using endoDPT, the above CT scanner, and a GE MRI scanner. This study found that the resolution of endoDPT was significantly higher than CT. The radiation dose of endoDPT was significantly lower than CT in the regions of the phantom that were not in the endoDPT field of view (FoV). Inside the endoDPT FoV, the radiation dose ranged from significantly less than to significantly greater than CT. The endoDPT images of the canine prostate specimens demonstrated qualitative improvements in resolution compared to CT and MRI, but endoDPT had difficulty in visualizing larger structures, such as the prostate border. Overall, this study has demonstrated endoDPT has high image resolution compared to typical methods of PCa imaging. Future work will be focused on development of a prototype system that improves scanning efficiency that can be used to optimize endoDPT and perform pre-clinical studies

Application of boundary detection information in breast tomosynthesis reconstruction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135006/1/mp1968.pd

Implementation of Digital Tomosynthesis in a Real Radiology System

The work included in this thesis is framed on one of the lines of research carried out by the Biomedical Imaging and Instrumentation Group from the Bioengineering and Aerospace Department of Universidad Carlos III de Madrid working jointly with the Gregorio Marañón Hospital. Its goal is to design and develop a new generation of Radiology Systems, valid for clinical and veterinary applications, through the research and development of innovative technologies in advanced image processing oriented to increase image quality, to reduce dose and to incorporate tomographic capabilities. The latter will allow bringing tomography to situations in which a CT system is not allowable due to cost issues or when the patient cannot be moved (for instance, during surgery or ICU). It may also be relevant to reduce the radiation dose delivered to the patient, if we can obtain a tomographic image from fewer projections than using a CT. In that context, this thesis deals with incorporating pseudo-tomographic capabilities, through a tomosynthesis protocol, in a radiology room originally designed for planar images: the NOVA FA digital radiography system developed by SEDECAL. The room consists of an X-ray generator, a vertical wall stand system, a mobile elevating table and an automatic ceiling suspension which allows the X-ray source to cover the whole volume of the room. Images are acquired using a flat panel detector connected through Wi-Fi to the computer station. Having evolved from conventional tomography, tomosynthesis produces section images at any depth from projections obtained at different angles along a linear sweep through the use of a suitable reconstruction algorithm. A workflow was established for the incorporation of tomosynthesis protocols to the NOVA FA system starting from the design of the protocol down to the reconstruction step. This required the understanding of the system and the development of several software tools. For the design of new protocols, a tomosynthesis module was incorporated to an in-house X- ray simulation tool programmed in Matlab and CUDA. As the X-ray room was built specifically for research, everything is manual and all the software is open. This system is designed only for planar radiography and, as a consequence, it is very cumbersome to incorporate a protocol that involves more than one projection. Therefore, a new software tool was implemented in Matlab that allows the translation of each of the source-detector positions corresponding to the tomosynthesis design to the geometrical parameters of the NOVA FA system and their automatic addition to its database. To obtain a tomographic image from the data acquire, a reconstruction tool was developed in Matlab with the ability to use several reconstruction algorithms including Shift-and-Add and Backprojection. Finally, two different evaluations were conducted: a geometric evaluation to assess the correlation between the simulation tool and the X-ray room and an evaluation of the complete workflow through the design and implementation of a simple tomosynthesis protocol using a PBU-50 body phantom developed by Kyoto Kagatu. The results of these evaluation studies showed the feasibility of the proposal. It should be noted that the work of this thesis has a clear application in industry, since it is part of a proof of concept of the new generation of radiology systems which will be commercialised worldwide by the company SEDECAL.Ingeniería Biomédic

Image reconstruction and imaging configuration optimization with a novel nanotechnology enabled breast tomosynthesis multi-beam X-ray system

Digital breast tomosynthesis is a new technology that provides three-dimensional information of the breast and makes it possible to distinguish the cancer from overlying breast tissues. We are dedicated to optimizing image reconstruction and imaging configuration for a new multi-beam parallel digital breast tomosynthesis prototype system. Several commonly used algorithms from the typical image reconstruction models which were used for iso-centric tomosynthesis systems were investigated for our multi-beam parallel tomosynthesis imaging system. The representative algorithms, including back-projection (BP), filtered back-projection (FBP), matrix inversion tomosynthesis reconstruction (MITS), maximum likelihood expectation maximization (MLEM), ordered-subset maximum likelihood expectation maximization (OS-MLEM), simultaneous algebraic reconstruction technique (SART), were implemented to fit our system design. An accelerated MLEM algorithm was proposed, which significantly reduced the running time but had the same image quality. Furthermore, two statistical variants of BP reconstruction were validated for our tomosynthesis prototype system. Experiments based on phantoms and computer simulations show that the prototype system combined with our algorithms is capable of providing three-dimensional information of the objects with good image quality and has great potentials to improve digital breast tomosynthesis technology. Four methodologies were employed to optimize the reconstruction algorithms and different imaging configurations for the prototype system. A linear tomosynthesis imaging analysis tool was used to investigate blurring-out reconstruction algorithms. Computer simulations of sphere and wire objects aimed at the performance of out-of-plane artifact removal. A frequency-domain-based methodology, relative NEQ(f) analysis, was investigated to evaluate the overall system performance based on the propagation of signal and noise. Conclusions were made to determine the optimal image reconstruction algorithm and imaging configuration of this new multi-beam parallel digital breast tomosynthesis prototype system for better image quality and system performance

Enhanced Digital Breast Tomosynthesis diagnosis using 3D visualization and automatic classification of lesions

Breast cancer represents the main cause of cancer-related deaths in women. Nonetheless, the mortality rate of this disease has been decreasing over the last three decades, largely due to the screening programs for early detection. For many years, both screening and clinical diagnosis were mostly done through Digital Mammography (DM). Approved in 2011, Digital Breast Tomosynthesis (DBT) is similar to DM but it allows a 3D reconstruction of the breast tissue, which helps the diagnosis by reducing the tissue overlap. Currently, DBT is firmly established and is approved as a stand-alone modality to replace DM. The main objective of this thesis is to develop computational tools to improve the visualization and interpretation of DBT data. Several methods for an enhanced visualization of DBT data through volume rendering were studied and developed. Firstly, important rendering parameters were considered. A new approach for automatic generation of transfer functions was implemented and two other parameters that highly affect the quality of volume rendered images were explored: voxel size in Z direction and sampling distance. Next, new image processing methods that improve the rendering quality by considering the noise regularization and the reduction of out-of-plane artifacts were developed. The interpretation of DBT data with automatic detection of lesions was approached through artificial intelligence methods. Several deep learning Convolutional Neural Networks (CNNs) were implemented and trained to classify a complete DBT image for the presence or absence of microcalcification clusters (MCs). Then, a faster R-CNN (region-based CNN) was trained to detect and accurately locate the MCs in the DBT images. The detected MCs were rendered with the developed 3D rendering software, which provided an enhanced visualization of the volume of interest. The combination of volume visualization with lesion detection may, in the future, improve both diagnostic accuracy and also reduce analysis time. This thesis promotes the development of new computational imaging methods to increase the diagnostic value of DBT, with the aim of assisting radiologists in their task of analyzing DBT volumes and diagnosing breast cancer

A comparative study of limitedâ angle coneâ beam reconstruction methods for breast tomosynthesis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134781/1/mp7543.pd