17 research outputs found

    Application of Wavelets and Principal Component Analysis in Image Query and Mammography

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    Breast cancer is currently one of the major causes of death for women in the U.S. Mammography is currently the most effective method for detection of breast cancer and early detection has proven to be an efficient tool to reduce the number of deaths. Mammography is the most demanding of all clinical imaging applications as it requires high contrast, high signal to noise ratio and resolution with minimal x-radiation. According to studies [36], 10% to 30% of women having breast cancer and undergoing mammography, have negative mammograms, i.e. are misdiagnosed. Furthermore, only 20%-40% of the women who undergo biopsy, have cancer. Biopsies are expensive, invasive and traumatic to the patient. The high rate of false positives is partly because of the difficulties in the diagnosis process and partly due to the fear of missing a cancer. These facts motivate research aimed to enhance the mammogram images (e.g. by enhancement of features such as clustered calcification regions which were found to be associated with breast cancer) , to provide CAD (Computer Aided Diagnostics) tools that can alert the radiologist to potentially malignant regions in the mammograms and to develope tools for automated classification of mammograms into benign and malignant classes. In this paper we apply wavelet and Principal Component analysis, including the approximate Karhunen Loeve aransform to mammographic images, to derive feature vectors used for classification of mammographic images from an early stage of malignancy. Another area where wavelet analysis was found useful, is the area of image query. Image query of large data bases must provide a fast and efficient search of the query image. Lately, a group of researchers developed an algorithm based on wavelet analysis that was found to provide fast and efficient search in large data bases. Their method overcomes some of the difficulties associated with previous approaches, but the search algorithm is sensitive to displacement and rotation of the query image due to the fact that wavelet analysis is not invariant under displacement and rotation. In this study we propose the integration of the Hotelling transform to improve on this sensitivity and provide some experimental results in the context of the standard alphabetic characters

    Position Ring System using Anger Type Detectors

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    Optimised Mammogram Displays for Improved Breast Cancer Detection

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    In current mammography practice, radiologists typically view mammograms in a symmetric, side-by-side, configuration in the belief that abnormalities will be made salient because they break the perceived symmetry. The literature on the use of symmetry as an aid to signal detection is limited and this thesis has taken a psychophysical approach to investigate the radiologist’s task of detecting a small mass (a blob) in paired mammogram backgrounds. Initial experiments used Gaussian white noise and synthetic mammogram backgrounds to test observer performance for the radiologist’s task using symmetric (side-by-side) displays and animated (the two images of a pair alternated sequentially in the same location) displays. The use of animated displays was then tested using real mammogram backgrounds in the subsequent experiments. The results showed that side-by-side presentation of paired images does not provide any benefit for the detection of a blob, whereas, alternated presentation enabled the observer to use the correlation present between the paired images to improve detection performance. The effect of alternation was not evident when applied to the task of detecting a small mass in real mammogram pairs and subsequent investigation suggested that the loss of effect resulted from the lack of scale invariance of real images. This meant that, regardless of the level of global correlation between two images, the localised correlation, at a region size reflecting the visual angle subtended by the fovea, was much lower. Thus, decorrelation by the visual system was ineffective and performance for the detection of a blob in the paired images was also ineffective. This thesis suggests that, whilst animated displays can be a powerful tool for the identification of differences between paired images, the underpinning mechanism of decorrelation makes them unsuited for mammograms where scale invariance means that correlation at local levels is a fraction of the global correlation level

    Deep learning in medical imaging and radiation therapy

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146980/1/mp13264_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146980/2/mp13264.pd

    Subjective Evaluation of the In-Line Phase-Sensitive Imaging Systems in Breast Cancer Screening and Diagnosis

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    Breast x-ray imaging remains the gold standard screening tool despite the various imaging modalities. The phase-sensitive breast imaging is an evolving technology that may provide higher diagnostic accuracy and potentially reduce the patient radiation dose. Many studies evaluate the performance of the In-line phase-sensitive breast imaging to improve this imaging modality further. Whereas radiologists are the end-users of this imaging technology, the primary goal of this dissertation project is to investigate the performance of human observers in varying conditions for further improvement of the in-line phase-sensitive x-ray imaging system. A CDMAM phantom and an ACR mammography phantom are used in the observer performance study to compare the high-energy in-line phase-sensitive system with a mid-energy system as an alternative approach to balancing the attenuation-based image contrast with the accuracy of single-projection PAD-base phase-retrieval. Additionally, a series of ROC studies are designed by a contrast-detail phantom to evaluate the diagnostic accuracy of digital breast tomosynthesis (DBT) and the phase-sensitive prototype imaging system (PBT). The area under the ROC curves (AUC) and partial area under the ROC curves (pAUC) are estimated as a figure of merits in the two systems, delivering the equivalent radiation doses. A two-alternative-forced choice (2AFC) study is also designed to determine the preferred image in identifying the suspicious lesions within a heterogeneous pattern acquired by the DBT and PBT systems under an equivalent radiation dose. The observer performance studies show that the mid-energy system has a potential advantage in providing a relatively higher image quality while the radiation dose is reduced in the mid-energy system compared with a high-energy system. The ROC study shows that the diagnostic accuracy of observers is more significant in the prototype PBT system than in a commercial DBT system, delivering the same radiation dose. The 2AFC study also revealed that observers prefer the PBT system in detecting and distinguishing the conspicuity of tumors in the images with structural noise, and the results were statistically significant. The dissertation also introduces a mathematical approach for estimating the half-value-layer (HVL) from measured or simulated x-ray spectra. The HVL measurement is expected to be less accurate or experimentally challenging in some clinical equipment or when a quick beam quality evaluation is needed. Additionally, the impact of varying thicknesses of external filtration is subjectively and objectively investigated to evaluate the feasibility of reducing the image acquisition time in a mid-energy system without compromising the observer's performance and detectability. The preliminary results from phase-contrast images suggest that an in-line phase-sensitive system operated at 59 kV shows a comparable image quality with the x-ray beams filtered by 1.3 mm and 2.5 mm-thick aluminum filters. This finding could help shorten the exposure time by 34% in the mid-energy system, where image blurring is a concern due to patient movement in a longer image acquisition time. In summary, and as expected, the subjective analyses of the in-line phase-sensitive imaging system align with the previous findings. However, the PBT imaging system may benefit from further improvement in image processing algorithms and optimizing the system with the most appropriate x-ray beam quality, considering the acquisition time, breast glandular composition, breast thickness, and different x-ray energies. Keywords: Phase-sensitive X-ray Imaging, Breast Imaging, Image Quality, Human Observer Performance Stud
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