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.

Breast cancer continues to be the most frequently diagnosed cancer in Canadian women. Currently, mammography is the clinically accepted best modality for breast cancer detection and the regular use of screening has been shown to contribute to the reduced mortality. However, mammography suffers from several drawbacks which limit its sensitivity and specificity. As a potential solution, digital breast tomosynthesis (DBT) uses a limited number (typically 10-20) of low-dose x-ray projections to produce a three-dimensional tomographic representation of the breast. The reconstruction of DBT images is challenged by such incomplete sampling. The purpose of this thesis is to evaluate the effect of image acquisition parameters on image quality of DBT for various reconstruction techniques and to optimize these, with three specific goals: A) Develop a better power spectrum estimator for detectability calculation as a task-based image quality index; B) Develop a paired-view algorithm for artifact removal in DBT reconstruction; and C) Increase dose efficiency in DBT by reducing random noise. A better power spectrum estimator was developed using a multitaper technique, which yields reduced bias and variance in estimation compared to the conventional moving average method. This gives us an improved detectability measurement with finer frequency steps. The paired-view scheme in DBT reconstruction provides better image quality than the commonly used sequential method. A simple ordering like the “side-to-side” method can achieve less artifact and higher image quality in reconstructed slices. The new denoising algorithm developed was applied to the projection views acquired in DBT before reconstruction. The random noise was markedly removed while the anatomic details were maintained. With the help of this artifact-removal technique used in reconstruction and the denoising method employed on the projection views, the image quality of DBT is enhanced and lesions should be more readily detectable.

The best way to conquer breast cancer is early detection of the disease. Research studies show that earlier detection results in the increase of life span of the affected person. Traditional two-dimensional mammography is the most prevalent method used in detecting breast cancer. Recently, a three-dimensional digital breast tomosynthesis (DBT) system has been created, which is hopeful to surpass the technology of traditional mammography systems. The DBT system can provide three-dimensional information, allowing physicians to reduce the amount of false negative screening in addition to better monitoring of breast cancer and to catch lesions that may be otherwise cancerous. In this research, the View Angle (VA) and number of projection images (N) were investigated and compared with parallel imaging configurations using two reconstruction algorithms, including Back Projection (BP) and Shift-And-Add (SAA). Modulation Transfer Function (MTF) analyses were conducted with both algorithms, in order to determine which method displayed better image qualities to ultimately improve the detection of breast cancer.

A tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT) é um exame radiográfico utilizado para o rastreamento do câncer de mama, que busca superar a limitação da sobreposição de tecidos existente na mamografia digital 2D. Nessa técnica são adquiridas projeções radiográficas em diferentes ângulos, que são processadas para a reconstrução do volume da mama. Um grande desafio é a elaboração dos algoritmos para a reconstrução tomográfica, visto que há um número limitado de projeções adquiridas com baixas doses de radiação, abrangendo uma estreita faixa de ângulo. Outro fator importante é o ruído presente nas imagens, que pode impactar o diagnóstico do câncer pelos radiologistas. Esse trabalho tem como objetivo apresentar uma ferramenta de reconstrução de imagens para DBT e fazer um estudo do comportamento do sinal e do ruído nas imagens reconstruídas. Os métodos analíticos de retroprojeção simples e filtrada, bem como os interativos de máxima verossimilhança e algébricos foram avaliados. A validação dos algoritmos de reconstrução foi feita por meio de métricas objetivas e as imagens reconstruídas foram comparadas com imagens obtidas a partir de um software de reconstrução para DBT desenvolvido pelo Food and Drug Administration (FDA). A partir das análises objetivas e visuais, demonstrou-se o potencial da ferramenta desenvolvida nesse trabalho. O ruído pós-reconstrução foi investigado através da aquisição de imagens de phantoms homogêneos, utilizando dois sistemas comerciais de DBT. As curvas de valor médio de pixel, a variância do ruído e a relação sinal-ruído seguiram o mesmo padrão já demonstrado para as projeções. A análise do espectro de potência do ruído demonstrou que o processo de reconstrução correlaciona o ruído para ambos os equipamentos. / Digital Breast Tomosynthesis (DBT) is a radiographic examination used for breast cancer screening, which seeks to overcome the tissue superposition in 2D digital mammography. In this technique, radiographic projections are acquired at different angles, which are processed for the reconstruction of the breast volume. A major challenge is the elaboration of algorithms for tomographic reconstruction since there are a limited number of projections acquired with low doses of radiation, covering a narrow-angle range. Another important factor is the noise present in this modality that can impact the diagnosis of tumors by radiologists. This work aims to present an image reconstruction toolbox for DBT and study the signal and noise behavior in the reconstructed slices. The analytical methods of simple and filtered back-projection, as well as the maximum likelihood and algebraic iterative methods were evaluated. The validation of the reconstruction algorithms was done by objective metrics and the reconstructed images were compared with the images obtained from a reconstruction software for DBT developed by the Food and Drug Administration (FDA). Through the objective and visual analysis, the potential of the toolbox developed in this work was demonstrated. The noise after reconstruction was investigated by means of the acquisition of homogeneous phantom images, using two commercial DBT systems. The mean pixel value, the noise variance and the signal-to-noise ratio follow the same curve shape already shown for the projection domain. The analysis of noise power spectrum demonstrated that the process of reconstruction correlates the noise for both systems used.

A novel imaging technology, digital breast tomosynthesis (DBT), is a technique that overcomes the tissue superposition limitation of conventional mammography by acquiring a limited number of X-ray projections from a narrow angular range, and combining these projections to reconstruct a pseudo-3D image. The emergence of DBT as a potential replacement or adjunct to mammographic screening mandates that solutions be found to two of its major limitations, namely X-ray scatter and mono-energetic reconstruction methods. A multi-faceted software-based approach to enhance the image quality of DBT imaging has the potential to increase the sensitivity and specificity of breast cancer detection and diagnosis. A scatter correction (SC) algorithm and a spectral reconstruction (SR) algorithm are both ready for implementation and clinical evaluation in a DBT system and exhibit the potential to improve image quality. A principal component analysis (PCA) based model of breast shape and a PCA model of X-ray scatter optimize the SC algorithm for the clinical realm. In addition, a comprehensive dosimetric characterization of a FDA approved DBT system has also been performed, and the feasibility of a new dual-spectrum, single-acquisition DBT imaging technique has also been evaluated.

Conventional 2D mammography was the most effective approach to detecting early stage breast cancer in the past decades of years. Tomosynthetic breast imaging is a potentially more valuable 3D technique for breast cancer detection. The limitations of current tomosynthesis systems include a longer scanning time than a conventional digital X-ray modality and a low spatial resolution due to the movement of the single X-ray source. Dr.Otto Zhou's group proposed the concept of stationary digital breast tomosynthesis (s-DBT) using a Carbon Nano-Tube (CNT) based X-ray source array. Instead of mechanically moving a single X-ray tube, s-DBT applies a stationary X-ray source array, which generates X-ray beams from different view angles by electronically activating the individual source prepositioned at the corresponding view angle, therefore eliminating the focal spot motion blurring from sources. The scanning speed is determined only by the detector readout time and the number of sources regardless of the angular coverage spans, such that the blur from patient's motion can be reduced due to the quick scan. S-DBT is potentially a promising modality to improve the early breast cancer detection by providing decent image quality with fast scan and low radiation dose. DBT system acquires a limited number of noisy 2D projections over a limited angular range and then mathematically reconstructs a 3D breast. 3D reconstruction is faced with the challenges of cone-beam and flat-panel geometry, highly incomplete sampling and huge reconstructed volume. In this research, we investigated several representative reconstruction methods such as Filtered backprojection method (FBP), Simultaneous algebraic reconstruction technique (SART) and Maximum likelihood (ML). We also compared our proposed statistical iterative reconstruction (IR) with particular prior and computational technique to these representative methods. Of all available reconstruction methods in this research, our proposed statistical IR appears particularly promising since it provides the flexibility of accurate physical noise modeling and geometric system description. In the following chapters, we present multiple key techniques of statistical IR to tomosynthesis imaging data to demonstrate significant image quality improvement over conventional techniques. These techniques include the physical modeling with a local voxel-pair based prior with the flexibility in its parameters to fine-tune image quality, the pre-computed parameter κ incorporated with the prior to remove the data dependence and to achieve a predictable resolution property, an effective ray-driven technique to compute the forward and backprojection and an over-sampled ray-driven method to perform high resolution reconstruction with a practical region of interest (ROI) technique. In addition, to solve the estimation problem with a fast computation, we also present a semi-quantitative method to optimize the relaxation parameter in a relaxed order-subsets framework and an optimization transfer based algorithm framework which potentially allows less iterations to achieve an acceptable convergence. The phantom data is acquired with the s-DBT prototype system to assess the performance of these particular techniques and compare our proposed method to those representatives. The value of IR is demonstrated in improving the detectability of low contrast and tiny micro-calcification, in reducing cross plane artifacts, in improving resolution and lowering noise in reconstructed images. In particular, noise power spectrum analysis (NPS) indicates a superior noise spectral property of our proposed statistical IR, especially in the high frequency range. With the decent noise property, statistical IR also provides a remarkable reconstruction MTF in general and in different areas within a focus plane. Although computational load remains a significant challenge for practical development, combined with the advancing computational techniques such as graphic computing, the superior image quality provided by statistical IR will be realized to benefit the diagnostics in real clinical applications.

Currently, mammography is the most common imaging technology used in breast screening. Low dose X-rays are passed through the breast to generate images called mammograms. One type of breast abnormality is a cluster of microcalcifications. Usually, in benign cases, microcalcifications result from the death of fat cells or are due to secretion by the lobules. However, in some cases, clusters of microcalcifications are indicative of early breast cancer, partly because of the secretions by cancer cells or the death of such cells. Due to the different attenuation characteristics of normal breast tissue and microcalcifications, the latter ideally appear as bright white spots and this allows detection and analysis for breast cancer classification. Microcalcification detection is one of the primary foci of screening and has led to the development of computer-aided detection (CAD) systems. However, a fundamental limitation of mammography is that it gives a 2D view of the tightly compressed 3D breast. The depths of entities within the breast are lost after this imaging process, even though the breast tissue is spread out as a result of the compression force applied to the breast. The superimposition of tissues can occlude cancers and this has led to the development of digital breast tomosynthesis (DBT). DBT is a three-dimensional imaging involving an X-ray tube moving in an arc around the breast, over a limited angular range, producing multiple images, which further undergo a reconstruction step to form a three-dimensional volume of breast. However, reconstruction remains the subject of research and small microcalcifications are "smeared" in depth by current algorithms, preventing detailed analysis of the geometry of a cluster. By using the geometry of the DBT acquisition system, we derive the "epipolar" trajectory of a microcalcification. As a first application of the epipolars, we develop a clustering algorithm after using the Hough transform to find corresponding points generated from a microcalcification. Noise points can also be isolated. In addition, we show how microcalcification projections can be detected adaptively. Epipolar analysis has also led to a novel detection algorithm for DBT using a Bayesian method, which estimates a maximum a posterior (MAP) labelling in each individual image and subsequently for all projections iteratively. Not only does this algorithm output the binary decision of whether a pixel is a microcalcification, it can predict the approximate depth of the microcalcification in the breast if it is. Based on the epipolar analysis, reconstruction of just a region of interest (ROI) e.g. microcalcification clusters is possible and it is more straightforward than any existing method using reconstruction slices. This potentially enables future classification of breast cancer when more clinical data becomes available.

Bröst består av mjölkkörtlar, subkutant fett och bindväv. Det finns också kärl och lymfa i brösten. Både män och kvinnor har bröst. Olika sjukdomar kan drabba brösten av benigna och maligna slag. Den mest använda undersökningsmetoden för att upptäcka bröstcancer är mammografi. Vid ytterligare undersökning av brösten kan digital bröst-tomosyntes (DBT) förekomma. DBT är en sorts begränsad vinkel-tomografi som producerar bilder på brösten i sektioner. Åsikter om DBT är motstridiga, en del studier säger att tomosyntes är bättre än mammografi gällande sensitivitet och andra säger att det är sämre eller ekvivalent. För att få kunskap om tomosyntes, mammografi och vad som skiljer i sensitivitet krävs det en sammanfattning av olika studier. Syftet med studien är att jämföra sensitivitet vid bröstundersökningar inom mammografi och tomosyntes. Via en systematisk litteraturstudie sammanfattas ett resultat utifrån kvantitativa artiklar som kvalitetsgranskas och analyseras. Arbetet har genomgått en etisk egengranskning. Resultatet skapades via hypotesprövning och SPSS och de påvisar att det finns en signifikant skillnad i sensitivitet mellan DBT och mammografi vilket innebär att DBT har högre sensitivitet sett till medelvärde och median.

O câncer de mama é a doença que mais acomete as mulheres em todo o mundo, sendo o tratamento mais eficaz se for diagnosticada em estágio inicial. A partir de 2011, nos programas de rastreamento de países desenvolvidos, vem sendo empregada uma nova modalidade de exame, a tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT), que possui diversas vantagens se comparada à mamografia digital. No exame, o médico radiologista busca por sinais suspeitos na imagem, como: nódulos, microcalcificações e distorção arquitetural mamária (DAM). Sendo que, este último pode representar o estágio mais inicial de um câncer em formação, podendo se manifestar antes da formação de qualquer outra lesão. No entanto, a DAM é difícil de ser detectada pois modifica o tecido mamário de forma sutil, não havendo qualquer formação de massa ou a borda definida. Os sistemas computacionais de auxílio ao diagnóstico (Computer-Aided Detection - CAD) vêm apresentando alto desempenho na detecção de nódulos e microcalcificações mamárias, mas para o caso da DAM, o desempenho ainda é insatisfatório. Algumas limitações são normalmente reportadas nos algoritmos adotados para detectar automaticamente a DAM. O presente trabalho tem por objetivo propor novas abordagens para aumentar a precisão dos métodos computacionais de detecção: o uso de descritores de micro-padrões local para discriminação de áreas suspeitas; redução de falsos-positivos; uso do volume 3D fornecido pelo exame de DBT e; uso de arquitetura de aprendizagem profunda para discriminação e classificação de regiões suspeitas. Os diversos testes efetuados em cada proposta mostraram que é possível melhorar as taxas de detecção da DAM, mesmo para imagens de DBT onde ainda não há um esquema computacional de detecção bem estabelecido. / Breast cancer is the disease that most affects women worldwide and is the most effective treatment if it is diagnosed at early stages. Since 2011, in developed countries screening programs has been employed a new exam, the digital breast tomosynthesis (DBT), which has several advantages compared to the digital mammography. In the exam, the radiologist looks for suspicious signs in the image such as masses, microcalcifications and architectural distortion of breast (ADB). Since the later may represent the earliest sign of a cancer in formation, it may manifests before the formation of any other lesion. However, ADB is difficult to be detected due to its subtly changes the breast tissue, with no mass or defined shape. Computer-aided detection (CAD) systems have shown good results in the detection of masses and microcalcifications, however, for ADB the performance is still poor. Several weakness are reported in the pipeline adopted to automatic detection of ADB. The present work aims to propose new approaches to increase the accuracy of the current CAD pipeline: the use of local micro-pattern descriptors to discriminate suspicious areas; false-positives reduction; automatic detection of ADB in DBT images using and tridimensionality of the exam and; use of deep learning architecture to discriminate and classify suspicious regions. The several tests performed on each proposal showed that it is possible to improve the detection rates even for DBT images where there is no established CAD pipeline.

The current thesis is focused on the study of tomosynthesis techniques applied on breast imaging, in order to improve the detection of breast lesions. Breast Tomosynthesis (BT) is a pseudo-three-dimensional (3D) x-ray imaging technique that provides reconstructed tomographic images from a set of angular projections taken in a limited arc around the breast, with dose levels similar to those of a two-view conventional mammography. Simulation studies and clinical trials suggest that BT is very useful for imaging the breast in an attempt to optimize the detection and characterization of lesions particularly in dense breasts and has the potential to reduce the recall rate. Reconstruction algorithms and acquisition parameters are critical for the quality of reconstructed slices. The aim of this research is to explore tomosynthesis modalities for breast imaging and evaluate them against existing mammographic techniques as well as to investigate the effect of reconstruction algorithms and acquisition parameters on the image quality of tomosynthetic slices. A specific aim and innovation of the study was to demonstrate the feasibility of combining BT and monochromatic radiation for 3D breast imaging, an approach that had not been studied thoroughly yet. For the purposes of this study a computer-based platform has been developed in Matlab incorporating reconstruction algorithms and filtering techniques for BT applications. It is fully parameterized and has a modular architecture for easy addition of new algorithms. Simulations studies with the XRayImaging Simulator and experimental work at ELETTRA Synchrotron facilities in Trieste, Italy, have been performed using software and complex hardware phantoms, of realistic shape and size, consisting of materials mimicking the breast tissue. The work has been carried out in comparison to conventional BT and mammography and demonstrates the feasibility of the studied new technique and the potential advantages of using BT with synchrotron modality for the detection of breast low- and high-contrast breast lesions such as masses and microcalcifications (μCs). Evaluations of both simulation and experimental tomograms demonstrated superior visibility of all reconstructed features using appropriately optimized filtered algorithms. Moreover, image quality and evaluation metrics are improved with extending the acquisition length for the masses. The visualization of μCs was found less sensitive to this parameter due to their high inherent contrast. Breast tomosynthesis shows advantages in visualizing features of small size within phantoms of increased thickness and especially in bringing into focus and localizing low-contrast masses hidden in a highly heterogeneous background with superimposed structures. Monochromatic beams can result in better tissue differentiation and in combination with BT can lead to improvement of features’ visibility, better detail and higher contrast. Monochromatic BT provided improved image quality at lower incident exposures, compared to conventional mammography, concerning mass detection and visibility of borders, which is important for their characterization, especially when they are spiculated. Overall it has been proved that while reducing the radiation dose, monochromatic beams combined with BT, result in an improvement of image quality. These findings are encouraging for the development of a tomosynthesis system based on monochromatic beams. / Η συγκεκριμένη διατριβή εστιάζει στη μελέτη των τεχνικών της τομοσύνθεσης όπως αυτές εφαρμόζονται στην απεικόνιση του μαστού, με στόχο την βελτίωση της ανίχνευσης των αλλοιώσεων του μαστού. Η τομοσύνθεση του μαστού είναι μια τεχνική ψευδό-τρισδιάστατης απεικόνισης με ακτίνες-χ που ανακατασκευάζει τομογραφικές εικόνες χρησιμοποιώντας μια σειρά προβολικών λήψεων υπό διαφορετικές γωνίες σε περιορισμένο τόξο γύρω από το μαστό και με δόσεις ακτινοβολίας παρόμοιες με εκείνες που απαιτούνται για τις δύο τυπικές λήψεις της κλασικής μαστογραφία. Μελέτες προσομοίωσης και κλινικές δοκιμές δείχνουν πως η τομοσύνθεση του μαστού βελτιώνει την απεικόνιση του μαστού, με αποτέλεσμα την καλύτερη ανίχνευση των αλλοιώσεων ειδικά σε πυκνούς μαστούς και αναμένεται ότι η εφαρμογή της θα μπορούσε να μειώσει την ανάγκη επανάληψης της εξέτασης. Οι αλγόριθμοι ανακατασκευής και οι παράμετροι λήψης των προβολικών εικόνων είναι μεγάλης σημασίας για την ποιότητα των ανακατασκευασμένων τομογραφικών εικόνων. Ο στόχος αυτής της έρευνας είναι να μελετήσει τεχνικές που βασίζονται στην τομογραφική απεικόνιση του μαστού και να τις συγκρίνει με υπάρχουσες τεχνικές μαστογραφίας καθώς και να διερευνήσει την επίδραση των αλγορίθμων ανακατασκευής και των παραμέτρων λήψης στην ποιότητα της ανακατασκευασμένης τομογραφικής εικόνας. Ένας συγκεκριμένος στόχος και καινοτομία αυτής της μελέτης ήταν να διερευνήσει πιθανά πλεονεκτήματα και να επιδείξει την σκοπιμότητα του συνδυασμού της τομοσύνθεσης του μαστού με μονοχρωματική ακτινοβολία που παράγεται από σύγχροτρον για την τρισδιάστατη απεικόνιση του μαστού, μία προσέγγιση που δεν είχε ακόμα μελετηθεί εκτενώς. Για τις ανάγκες αυτής της μελέτης αναπτύχθηκε στο Matlab μια πλατφόρμα που ενσωματώνει αλγορίθμους ανακατασκευής και τεχνικές φιλτραρίσματος για τομοσύνθεση μαστού. Η εφαρμογή είναι πλήρως παραμετροποιημένη και σχεδιασμένη ώστε να είναι εύκολη η προσθήκη νέων αλγορίθμων. Προσομοιώσεις με τη χρήση του προσομοιωτή XRayImagingSimulator καθώς και πειραματικές μελέτες στις εγκαταστάσεις σύγχροτρον ELETΤRA, στην Τεργέστη της Ιταλίας έχουν πραγματοποιηθεί, με χρήση απλών και σύνθετων ομοιωμάτων μαστού, μιμούμενα τις ιδιότητες του ιστού του μαστού, με ρεαλιστικό μέγεθος και σχήμα. Οι μελέτες έχουν πραγματοποιηθεί σε σύγκριση με την τυπική τομοσύνθεση μαστογραφία και δείχνουν πόσο εφικτή είναι η νέα τεχνική και τα δυνητικά πλεονεκτήματα της τομοσύνθεσης του μαστού με χρήση μονοχρωματικής ακτινοβολίας για την εύρεση χαμηλής και υψηλής αντίθεσης αλλοιώσεων όπως μάζες και μικροαποτιτανώσεις. Εκτιμήσεις των τομογραφικών εικόνων που έχουν προκύψει τόσο από προσομοιώσεις όσο και από πειράματα δείχνουν βελτιωμένη απεικόνιση όλων των ανακατασκευασμένων στοιχείων ενδιαφέροντος με χρήση κατάλληλων βελτιστοποιημένων φίλτρων. Επιπλέον, η ποιότητα της εικόνας βελτιώνεται με τη διεύρυνση του τόξου λήψης για τις μάζες, ενώ η απεικόνιση των μικροαποτιτανώσεων βρέθηκε να είναι λιγότερο ευαίσθητη σε αυτή τη παράμετρο λόγω της υψηλότερης αντίθεσης που έχουν σε σχέση με τον περιβάλλοντα φυσιολογικό ιστό του μαστού. Η τομοσύνθεση του μαστού φάνηκε να έχει πλεονεκτήματα στην απεικόνιση αλλοιώσεων μικρού μεγέθους και πιο συγκεκριμένα στο να διακρίνει και να ανιχνεύει χαμηλής αντίθεσης μάζες, μέσα σε πυκνούς μαστούς με έντονα ετερογενή σύσταση, μετριάζοντας τα προβλήματα επικάλυψης. Η μονοχρωματική ακτινοβολία μπορεί να προσφέρει καλύτερη διαφοροποίηση των ιστών του μαστού και σε συνδυασμό με την τομοσύνθεση μπορεί να οδηγήσει στην βελτίωση της απεικόνισης των αλλοιώσεων και στην παραγωγή εικόνων με καλύτερη λεπτομέρεια και υψηλότερη αντίθεση. Γενικά βρέθηκε ότι η μονοχρωματική τομοσύνθεση του μαστού παρέχει βελτιωμένη ποιότητα εικόνας, σε σύγκριση με την κλασική μαστογραφία, όσον αφορά την ανίχνευση όγκων και την ορατότητα των περιγραμμάτων τους, που είναι σημαντική για τον χαρακτηρισμό των μαζών, ειδικά όταν δεν έχουν καλώς καθορισμένα όρια. Συνολικά η μελέτη αυτή έδειξε ότι ακόμα και με μικρότερη δόση ακτινοβολίας, η χρήση μονοχρωματικής ακτινοβολίας σε συνδυασμό με την τομοσύνθεση του μαστού, έχουν ως αποτέλεσμα την βελτίωση της εικόνας, γεγονός που είναι ενθαρρυντικό για την ανάπτυξη ενός συστήματος τομοσύνθεσης βασισμένο σε ακτίνες-χ μονοχρωματικής δέσμης.