Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms

PURPOSE: We develop a practical, iterative algorithm for image-reconstruction in under-sampled tomographic systems, such as digital breast tomosynthesis (DBT). METHOD: The algorithm controls image regularity by minimizing the image total $p$-variation (TpV), a function that reduces to the total variation when $p=1.0$ or the image roughness when $p=2.0$. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets (POCS). The fact that the tomographic system is under-sampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) reduction of the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in under-sampled tomography. RESULTS: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. CONCLUSION: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.Comment: Submitted to Medical Physic

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm

The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in the article, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity X-ray illumination is presented.Comment: Resubmitted to Physics in Medicine and Biology. Text has been modified according to referee comments, and typos in the equations have been correcte

Selectiveâ diffusion regularization for enhancement of microcalcifications in digital breast tomosynthesis reconstruction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134765/1/mp5851.pd

DEVELOPMENT OF IN VITRO SOMACLONAL VARIATION FOR PELARGONIUM GRAVEOLENS L’HERIT, AIT

In vitro somaclonal variation via callus is considered as one of the most effective tool for improvement of vegetative propagated crops. Different combinations of cytokinine (BA) and auxine (NAA) were used to induce somaclonal variation from leaf explants of the Egyptian geranium cultivar, Pelargonium graveolens L’Herit, Ait. El Qanater El khayria cv.8. Callus induction and regenerated shoots from callus were evaluated; 2.5 mg/L BA and 0.5 mg/L NAA was the optimal for callus induction and number of regenerated shoots. The obtained plantlets were acclimatized under glasshouse conditions with 80% to 90% survival and were transferred to the open field. The evaluation of growth traits and oil analysis were done for the new 13 clones compared with the mother plant in randomized block design for two successive seasons. Characterization of these new clones for morphological traits and essential oil yield and quality demonstrated the induction of variability in negative and positive directions in some characteristics in comparison with the mother plant. Clone no.7 was the superior clone in herb 2264.7 & 2357.3 g/plant and oil yield 2.436 & 3.065 ml/plant in first and second season, respectively, than the mother plant and other new clones with acceptable content of citronellol 25.63% and geraniol 26.52% as a parameter for volatile oil quality. The genetic variation of the new geranium clones were tested using SRAP technique based on  PCR, the polymorphism was detected using 16  pairs of SRAP primers in combinations as forward and reverse. The genetic differences between new clones and the mother plant were ascertained with SRAP primer pair (me2 em4); a unique profile for clone no.7 was detected in SRAP analysis. The similarity percentage varied between 66.7% to 100% homologies among the new clones and their mother plant. The presence of genetic variation between new clones and the mother plant proved that the calliclones were somaclonal mutants, and the geranium cultivar, El Qanater El khayria cv.8, was improved for high yield in herb and essential oil

A parametric level-set method for partially discrete tomography

This paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We represent the geometry of the anomaly using a level-set function, which we represent using radial basis functions. We pose the reconstruction problem as a bi-level optimization problem in terms of the background and coefficients for the level-set function. To constrain the background reconstruction we impose smoothness through Tikhonov regularization. The bi-level optimization problem is solved in an alternating fashion; in each iteration we first reconstruct the background and consequently update the level-set function. We test our method on numerical phantoms and show that we can successfully reconstruct the geometry of the anomaly, even from limited data. On these phantoms, our method outperforms Total Variation reconstruction, DART and P-DART.Comment: Paper submitted to 20th International Conference on Discrete Geometry for Computer Imager

GPU-based Iterative Cone Beam CT Reconstruction Using Tight Frame Regularization

X-ray imaging dose from serial cone-beam CT (CBCT) scans raises a clinical concern in most image guided radiation therapy procedures. It is the goal of this paper to develop a fast GPU-based algorithm to reconstruct high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose. For this purpose, we have developed an iterative tight frame (TF) based CBCT reconstruction algorithm. A condition that a real CBCT image has a sparse representation under a TF basis is imposed in the iteration process as regularization to the solution. To speed up the computation, a multi-grid method is employed. Our GPU implementation has achieved high computational efficiency and a CBCT image of resolution 512\times512\times70 can be reconstructed in ~5 min. We have tested our algorithm on a digital NCAT phantom and a physical Catphan phantom. It is found that our TF-based algorithm is able to reconstrct CBCT in the context of undersampling and low mAs levels. We have also quantitatively analyzed the reconstructed CBCT image quality in terms of modulation-transfer-function and contrast-to-noise ratio under various scanning conditions. The results confirm the high CBCT image quality obtained from our TF algorithm. Moreover, our algorithm has also been validated in a real clinical context using a head-and-neck patient case. Comparisons of the developed TF algorithm and the current state-of-the-art TV algorithm have also been made in various cases studied in terms of reconstructed image quality and computation efficiency.Comment: 24 pages, 8 figures, accepted by Phys. Med. Bio

Beam Orientation Optimization for Intensity Modulated Radiation Therapy using Adaptive l1 Minimization

Beam orientation optimization (BOO) is a key component in the process of IMRT treatment planning. It determines to what degree one can achieve a good treatment plan quality in the subsequent plan optimization process. In this paper, we have developed a BOO algorithm via adaptive l_1 minimization. Specifically, we introduce a sparsity energy function term into our model which contains weighting factors for each beam angle adaptively adjusted during the optimization process. Such an energy term favors small number of beam angles. By optimizing a total energy function containing a dosimetric term and the sparsity term, we are able to identify the unimportant beam angles and gradually remove them without largely sacrificing the dosimetric objective. In one typical prostate case, the convergence property of our algorithm, as well as the how the beam angles are selected during the optimization process, is demonstrated. Fluence map optimization (FMO) is then performed based on the optimized beam angles. The resulted plan quality is presented and found to be better than that obtained from unoptimized (equiangular) beam orientations. We have further systematically validated our algorithm in the contexts of 5-9 coplanar beams for 5 prostate cases and 1 head and neck case. For each case, the final FMO objective function value is used to compare the optimized beam orientations and the equiangular ones. It is found that, our BOO algorithm can lead to beam configurations which attain lower FMO objective function values than corresponding equiangular cases, indicating the effectiveness of our BOO algorithm.Comment: 19 pages, 2 tables, and 5 figure

Sequence and structure of the mouse gene coding for the largest neurofilament subunit.

We have determined the complete nucleotide sequence of the mouse gene encoding the neurofilament NF-H protein. The C-terminal domain of NF-H is very rich in charged amino acids (aa) and contains a 3-aa sequence, Lys-Ser-Pro, that is repeated 51 times within a stretch of 368 aa. The location of this serine-rich repeat in the phosphorylated domain of NF-H indicates that it represents the major protein kinase recognition site. The nfh gene shares two common intron positions with the nfl and nfm genes, but has an additional intron that occurs at a location equivalent to one of the introns in non-neuronal intermediate filament-coding genes. This additional nfh intron may have been acquired via duplication of a primordial intermediate filament gene