213 research outputs found

    Breast Tomosynthesis: Aspects on detection and perception of simulated lesions

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    The aim of this thesis was to investigate aspects on detectability of simulated lesions (microcalcifications and masses) in digital mammography (DM) and breast tomosynthesis (BT). Perception in BT image volumes were also investigated by evaluating certain reading conditions. The first study concerned the effect of system noise on the detection of masses and microcalcification clusters in DM images using a free-response task. System noise has an impact on image quality and is related to the dose level. It was found to have a substantial impact on the detection of microcalcification clusters, whereas masses were relatively unaffected. The effect of superimposed tissue in DM is the major limitation hampering the detection of masses. BT is a three-dimensional technique that reduces the effect of superimposed tissue. In the following two studies visibility was quantified for both imaging modalities in terms of the required contrast at a fixed detection performance (92% correct decisions). Contrast detail plots for lesions with sizes 0.2, 1, 3, 8 and 25 mm were generated. The first study involved only an in-plane BT slice, where the lesion centre appeared. The second study repeated the same procedure in BT image volumes for 3D distributed microcalcification clusters and 8 mm masses at two dose levels. Both studies showed that BT needs substantially less contrast than DM for lesions above 1 mm. Furthermore, the contrast threshold increased as the lesion size increased for both modalities. This is in accordance with the reduced effect of superimposed tissue in BT. For 0.2 mm lesions, substantially more contrast was needed. At equal dose, DM was better than BT for 0.2 mm lesions and microcalcification clusters. Doubling the dose substantially improved the detection in BT. Thus, system noise has a substantial impact on detection. The final study evaluated reading conditions for BT image volumes. Four viewing procedures were assessed: free scroll browsing only or combined with initial cine loops at frame rates of 9, 14 and 25 fps. They were viewed on a wide screen monitor placed in vertical or horizontal positions. A free-response task and eye tracking were utilized to record the detection performance, analysis time, visual attention and search strategies. Improved reading conditions were found for horizontally aligned BT image volumes when using free scroll browsing only or combined with a cine loop at the fastest frame rate

    Fuzzy technique for microcalcifications clustering in digital mammograms

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    Background Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could turn out to be very useful in breast cancer control. Methods In this paper we present a potentially powerful microcalcifications cluster enhancement method applicable to digital mammograms. The segmentation phase employs a form filter, obtained from LoG filter, to overcome the dependence from target dimensions and to optimize the recognition efficiency. A clustering method, based on a Fuzzy C-means (FCM), has been developed. The described method, Fuzzy C-means with Features (FCM-WF), was tested on simulated clusters of microcalcifications, implying that the location of the cluster within the breast and the exact number of microcalcifications are known.The proposed method has been also tested on a set of images from the mini-Mammographic database provided by Mammographic Image Analysis Society (MIAS) publicly available. Results The comparison between FCM-WF and standard FCM algorithms, applied on both databases, shows that the former produces better microcalcifications associations for clustering than the latter: with respect to the private and the public database we had a performance improvement of 10% and 5% with regard to the Merit Figure and a 22% and a 10% of reduction of false positives potentially identified in the images, both to the benefit of the FCM-WF. The method was also evaluated in terms of Sensitivity (93% and 82%), Accuracy (95% and 94%), FP/image (4% for both database) and Precision (62% and 65%). Conclusions Thanks to the private database and to the informations contained in it regarding every single microcalcification, we tested the developed clustering method with great accuracy. In particular we verified that 70% of the injected clusters of the private database remained unaffected if the reconstruction is performed with the FCM-WF. Testing the method on the MIAS databases allowed also to verify the segmentation properties of the algorithm, showing that 80% of pathological clusters remained unaffected

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

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    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

    The impact of simulated motion blur on breast cancer detection performance in full field digital mammography (FFDM)

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    Objective: Full-field Digital Mammography (FFDM) is employed in breast screening for the early detection of breast cancer. High quality, artefact free, diagnostic images are crucial to the accuracy of this process. Unwanted motion during the image acquisition phase and subsequent image blurring is an unfortunate occurrence in some FFDM images. The research detailed in this thesis seeks to understand the impact of motion blur on cancer detection performance in FFDM images using novel software to perform simulation of motion, an observer study to measure the lesion detection performance and physical measures to assess the impact of simulated motion blur on image characteristics of the lesions. Method: Seven observers (15±5 years’ reporting experience) evaluated 248 cases (62 containing malignant masses, 62 containing malignant microcalcifications and 124 normal cases) for three conditions: no motion blur (0.0 mm) and two magnitudes of simulated motion blur (0.7 mm and 1.5 mm). Abnormal cases were biopsy proven. A free-response observer study was conducted to compare lesion detection performance for the three conditions. Equally weighted jackknife alternative free-response receiver operating characteristic (wJAFROC) was used as the figure of merit. A secondary analysis of data was deemed important to simulate ‘double reporting’. In this secondary analysis, six of the observers are combined with the seventh observer to evaluate the impact of combined free-response data for lesion detection and to assess if combined two observers data could reduce the impact of simulated motion blur on detection performance. To compliment this, the physical characteristics of the lesions were obtained under the three conditions in order to assess any change in characteristics of the lesions when blur is present in the image. The impact of simulated motion blur on physical characteristics of malignant masses was assessed using a conspicuity index; for microcalcifications, a new novel metric, known as dispersion index, was used. Results: wJAFROC analysis found a statistically significant difference in lesion detection performance for both masses (F (2,22) = 6.01, P=0.0084) and microcalcifications (F(2,49) = 23.14, P<0.0001). For both lesion types, the figure of merit reduced as the magnitude of simulated motion blur increased. Statistical differences were found between some of the pairs investigated for the detection of masses (0.0mm v 0.7mm, and 0.0mm v 1.5mm) and all pairs for microcalcifications (0.0 mm v 0.7 mm, 0.0 mm v 1.5 mm, and 0.7 mm v 1.5 mm). No difference was detected between 0.7 mm and 1.5 mm for masses. For combined two observers’ data of masses, there was no statistically significant difference between single and combined free-response data for masses (F(1,6) = 4.04, p=0.1001, -0.031 (-0.070, 0.008) [treatment difference (95% CI)]. For combined data of microcalcifications, there was a statistically significant difference between single and combined free-response data (F(1,6) = 12.28, p=0.0122, -0.056 (-0.095, -0.017) [treatment difference (95% CI)]. Regarding the physical measures of masses, conspicuity index increases as the magnitude of simulated motion blur increases. Statistically significant differences were demonstrated for 0.0–0.7 mm t(22)=-6.158 (p<0.000); 0.0–1.5 mm t(22)=-6.273 (p<0.000); and 0.7–1.5 mm (t(22)=-6.231 (p<0.000). Lesion edge angle decreases as the magnitude of simulated motion blur increases. Statistically significant differences were demonstrated for 0.0–0.7 mm t(22)=3.232 (p<0.004); for 0.0–1.5 mm t(22)=6.592 (p<0.000); and 0.7–1.5mm t(22)=2.234 (p<0.036). For the grey level change there was no statistically significant difference as simulated motion blur increases to 0.7 and then to 1.5mm. For image noise there was a statistically significant difference, where noise reduced as simulated motion blur increased: 0.0–0.7 mm t(22)=22.95 (p<0.000); 0.0–1.5mm t(22)=24.66 (p<0.000); 0.7–1.5 mm t(22)=18.11 (p<0.000). For microcalcifications, simulated motion blur had a negative impact on the ‘dispersion index’. Conclusion: Mathematical simulations of motion blur resulted in a statistically significant reduction in lesion detection performance. This reduction in performance could have implications for clinical practice. Simulated motion blur has a negative impact on the edge angle of breast masses and a negative impact on the image characteristics of microcalcifications. These changes in the image lesion characteristics appear to have a negative effect on the visual identification of breast cancer

    Diagnostic and Interventional Radiology in a breast centre

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    Topic of the thesis is the analysis of three key aspects of diagnostic and interventional radiology in a Breast Center: 1 - monitoring of the radiation dose delivered by mammography; 2 – integrated diagnostic approach conducted together by radiologists and surgeons (joint CORD; 3 - interdisciplinary meetings. Radiation dose monitoring Mammography is still considered the most effective imaging technique for the early detection of breast cancer and for mortality reduction. The parameter for estimating the absorbed dose is the average glandular dose. The purpose of this section of the thesis is to present the data collected from three mammography units in the period from January 1 to May 31. A dose monitoring software (TQM) was used that was able to automatically detect relevant indices from X-ray equipments and to analyze the data in terms of variability of dosimetric behaviours. The “joint CORD” In the period from January 16 to April 11, a weekly session handled by a junior breast surgeon and a senior Radiology resident (joint CORD) was established. The aim of this session was to optimize the path within the Breast Centre of the patients with urgent referral and nonspecific symptoms. In fact, for these patients it is likely that the final diagnosis can be already reached with a clinical breast examination and a breast ultrasonography. Twelve sessions of joint CORD were performed, that included 95 patients (average: 7.9 patients for each session). Of the 95 patients who had access to this service, 33 had an examination performed elsewhere with detection of suspicious nodules or were controls at 6 months of multiple fibroadenomatosis; 20 came for palpable lumps; 16 for unilateral or bilateral breast pain; 5 for mastitis; 5 for swelling / hyperemia or collection after QUART; 4 for secretion (milky); and 12 for various reasons (axillary swelling, screening prior hormonal therapies, skin nodule, adenoma of the nipple). Of the 95 patients, besides ultrasound and clinical breast examination, 24 (25.2%) underwent mammography, 6 (6.3%) underwent MRI, and 2 (2, 1%) underwent stereotactic biopsy. Twentythree US-guided cytological examinations were performed (24.2%): in 21 cases of nodules and in 2 cases of mammary secretions. The results of cytology were: 15 C2 (benign findings) with the conclusion of the diagnostic iter; 2 C3 (probably benign findings); 4 C1 (inadequate sampling). The joint CORD allowed patients to finish their diagnostic workup in a single access, thus dramatically reducing the time they spent in the breast imaging center. Interdisciplinary meetings Were conducted interdisciplinary meetings (with breast radiologists and surgeons) on a weekly basis starting from January 17. This section of the thesis analyzes the period from January 17 to March 27. The cases discussed were tabulated to analyze the most frequent causes of problems, possible solutions and improvements for clinical practice. Eleven meetings were held, discussing a total of 48 cases (average: 4.36 cases discussed per meeting). Of the 48 cases discussed, 11 (22.9%) did not reach a cyto-histological conclusive diagnosis, 9 (18.7%) had an underlying lack of communication between radiologists and surgeons, 8 (16.6%) required a further biopsy, 6 (12.5%) had an improper use of MRI , 5 (10.4%) required additional MRI, 3 (6.25%) required a shared decision between radiologists and surgeons, 2 (4.1%) had a PET inappropriately performed, 2 (4.1%) were considered inappropriate for surgical evaluation, and 1 (2.07%) required a new mammography

    Mammography

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    In this volume, the topics are constructed from a variety of contents: the bases of mammography systems, optimization of screening mammography with reference to evidence-based research, new technologies of image acquisition and its surrounding systems, and case reports with reference to up-to-date multimodality images of breast cancer. Mammography has been lagged in the transition to digital imaging systems because of the necessity of high resolution for diagnosis. However, in the past ten years, technical improvement has resolved the difficulties and boosted new diagnostic systems. We hope that the reader will learn the essentials of mammography and will be forward-looking for the new technologies. We want to express our sincere gratitude and appreciation?to all the co-authors who have contributed their work to this volume

    A semi-empirical model for scatter field reduction in digital mammography

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    X-ray mammography is the gold standard technique in breast cancer screening programmes. One of the main challenges that mammography is still facing is scattered radiation, which degrades the quality of the image and complicates the diagnosis process. Anti-scatter grids, the main standard physical scattering reduction technique, have some unresolved challenges as they increase the dose delivered to the patient, do not remove all the scattered radiation and increase the cost of the equipment. Alternative scattering reduction methods based on post-processing algorithms, have lately been under investigation. This study is concerned with the use of image post-processing to reduce the scatter contribution in the image, by convolving the primary plus scatter image with kernels obtained from simplified Monte Carlo (MC) simulations. The proposed semi-empirical approach uses up to five thickness-dependant symmetric kernels to accurately estimate the scatter contribution of different areas of the image. Single breast thickness-dependant kernels can over-estimate the scatter signal up to 60%, while kernels adapting to local variations have to be modified for each specific case adding high computational costs. The proposed method reduces the uncertainty to a 4%-10% range for a 35-70 mm breast thickness range, making it a very efficient, case-independent scatter modelling technique. To test the robustness of the method, the scattered corrected image has been successfully compared against full MC simulations for a range of breast thicknesses. In addition, clinical images of the 010A CIRS phantom were acquired with a mammography system with and without the presence of the anti-scatter grid. The grid-less images were post-processed and their quality was compared against the grid images, by evaluating the contrast-to-noise ratio and variance ratio using several test objects, which simulate calcifications and tumour masses. The results obtained show that the method reduces the scatter to similar levels than the anti-scatter grids
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