Evaluation of a Multi-Scale Enhancement Protocol for Digital Mammography

We have carried out a receiver operating characteristics (ROC) study for the enhancement of mammographic features in digitized mammograms. The study evaluated the benefits of multi-scale enhancement methods in terms of diagnostic performance of radiologists. The enhancement protocol relied on multi-scale expansions and non-linear enhancement functions. Dyadic spline wavelet functions (first derivative of a cubic spline) were used together with a sigmoidal non-linear enhancement function. We designed a computer interface on a softcopy display and performed an ROC study with three radiologists, who specialized in mammography. Clinical cases were obtained from a national mammography database of digitized radiographs prepared by the University of South Florida (USF) and Harvard Medical School. Our study focused on dense mammograms, i.e. mammograms of density 3 and 4 on the American College of Radiology (ACR) breast density rating, which are the most difficult cases in screening, were selected. To compare the performance of radiologists with and without using multi-scale enhancement, two groups of 30 cases each were diagnosed. Each group contained 15 cases of cancerous and 15 cases of normal mammograms. Conventional ROC analysis was applied, and the resulting ROC curves indicated improved diagnostic performance when radiologists used multi-scale non-linear enhancement

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

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

Optimised Mammogram Displays for Improved Breast Cancer Detection

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

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

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

Patterns of injury and violence in Yaoundé Cameroon: an analysis of hospital data.

BackgroundInjuries are quickly becoming a leading cause of death globally, disproportionately affecting sub-Saharan Africa, where reports on the epidemiology of injuries are extremely limited. Reports on the patterns and frequency of injuries are available from Cameroon are also scarce. This study explores the patterns of trauma seen at the emergency ward of the busiest trauma center in Cameroon's capital city.Materials and methodsAdministrative records from January 1, 2007, through December 31, 2007, were retrospectively reviewed; information on age, gender, mechanism of injury, and outcome was abstracted for all trauma patients presenting to the emergency ward. Univariate analysis was performed to assess patterns of injuries in terms of mechanism, date, age, and gender. Bivariate analysis was used to explore potential relationships between demographic variables and mechanism of injury.ResultsA total of 6,234 injured people were seen at the Central Hospital of Yaoundé's emergency ward during the year 2007. Males comprised 71% of those injured, and the mean age of injured patients was 29 years (SD = 14.9). Nearly 60% of the injuries were due to road traffic accidents, 46% of which involved a pedestrian. Intentional injuries were the second most common mechanism of injury (22.5%), 55% of which involved unarmed assault. Patients injured in falls were more likely to be admitted to the hospital (p < 0.001), whereas patients suffering intentional injuries and bites were less likely to be hospitalized (p < 0.001). Males were significantly more likely to be admitted than females (p < 0.001)DiscussionPatterns in terms of age, gender, and mechanism of injury are similar to reports from other countries from the same geographic region, but the magnitude of cases reported is high for a single institution in an African city the size of Yaoundé. As the burden of disease is predicted to increase dramatically in sub-Saharan Africa, immediate efforts in prevention and treatment in Cameroon are strongly warranted