89 research outputs found

    Mass detection on mammograms: signal variations and performance changes for human and model observers

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    We studied the influence of signal variability on human and model observer performances for a detection task with mammographic backgrounds and computer generated clustered lumpy backgrounds (CLB). We used synthetic yet realistic masses and backgrounds that have been validated by radiologists during previous studies, ensuring conditions close to the clinical situation. Four trained non-physician observers participated in two-alternative forced-choice (2-AFC) experiments. They were asked to detect synthetic masses superimposed on real mammographic backgrounds or CLB. Separate experiments were conducted with sets of benign and malignant masses. Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) experiments. In the latter case, the signal was chosen randomly for each of the 1,400 2-AFC trials (image pairs) among a set of 50 masses with similar dimensions, and the observers did not know which signal was present. Human observers' results were then compared with model observers (channelized Hotelling with Difference-of-Gaussian and Gabor channels) in the same experimental conditions. Results show that the performance of the human observers does not differ significantly when benign masses are superimposed on real images or on CLB with locally matched gray level mean and standard deviation. For both benign and malignant masses, the performance does not differ significantly between SKE and SKS experiments, when the signals' dimensions do not vary throughout the experiment. However, there is a performance drop when the SKS signals' dimensions vary from 5.5 to 9.5 mm in the same experiment. Noise level in the model observers can be adjusted to reproduce human observers' proportion of correct answers in the 2-AFC task within 5% accuracy for most condition

    Impact of variations in physical parameters on glow curves for planchet heating of TL dosimeters

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    This study consists of a theoretical analysis of the directional planchet heating of Thermoluminescent Dosimeters (TLD) with an emphasis on influence of radiation field type, TL material properties, and heating scheme parameters on the resulting glow curve. Computer software is developed to simulate the thermal conduction and TL production processes in a planchet-heated TLD chip. The results of the simulation are benchmarked to previous experimental findings for a LiF TLD and excellent agreement is obtained. The system thermophysical parameters and initial depth-dose distribution in the TLD are varied and the position of the main glow peak and integral glow are examined. A demonstration is given of how a set of thermophysical parameters may provide information about the depth-dose distribution in the TLD and how variation in the values of these parameters may limit the reconstruction of this depth-dose information.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31122/1/0000018.pd

    Digital chest radiography: an update on modern technology, dose containment and control of image quality

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    The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems

    Study of Radiologic Technologists’ Perceptions of Picture Archiving and Communication System (PACS) Competence and Educational Issues in Western Australia

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    Although the implementation of picture archiving and communication system (PACS) could increase productivity of radiology departments, this depends on factors such as the PACS competence of radiologic technologists (RTs). The purpose of this study was to investigate the RTs’ perceptions of PACS competence and educational issues in Western Australia (WA). A hardcopy questionnaire was distributed to WA RTs for obtaining their perceptions of PACS competence and educational issues. Descriptive (percentage of frequency, mean and standard deviation) and inferential statistics (t test and analysis of variance) were used to analyze the responses of the multiple choice and five-point scale questions from the returned questionnaires. The questionnaire response rate was 57.7 % (173 out of 300). The mean values of all PACS competence questions except questions 2e–g are in the range of 3.9–4.9, i.e., around competent to very competent. Participants indicated they received adequate PACS training (mean 3.8). Statistically significant variables influencing RTs’ perceptions of their PACS competence and educational issues including the age (p < 0.01), gender (p < 0.05), years of practice (p < 0.005–0.05), primary duty (p < 0.05), medical imaging qualification (p < 0.001), general computer skills (p < 0.001), and type of PACS education received (p < 0.001–0.05). The WA RTs indicated that they were competent in using the modality workstation, PACS and radiology information system, and received adequate training. However, future PACS education programs should be tailored to different RTs’ groups. For example, multiple training modules might be necessary to support the PACS competence development of older RTs and those with lower general computer literacy

    Computed Tomography Imaging of Primary Lung Cancer in Mice Using a Liposomal-Iodinated Contrast Agent

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    To investigate the utility of a liposomal-iodinated nanoparticle contrast agent and computed tomography (CT) imaging for characterization of primary nodules in genetically engineered mouse models of non-small cell lung cancer.Primary lung cancers with mutations in K-ras alone (Kras(LA1)) or in combination with p53 (LSL-Kras(G12D);p53(FL/FL)) were generated. A liposomal-iodine contrast agent containing 120 mg Iodine/mL was administered systemically at a dose of 16 ”l/gm body weight. Longitudinal micro-CT imaging with cardio-respiratory gating was performed pre-contrast and at 0 hr, day 3, and day 7 post-contrast administration. CT-derived nodule sizes were used to assess tumor growth. Signal attenuation was measured in individual nodules to study dynamic enhancement of lung nodules.A good correlation was seen between volume and diameter-based assessment of nodules (R(2)>0.8) for both lung cancer models. The LSL-Kras(G12D);p53(FL/FL) model showed rapid growth as demonstrated by systemically higher volume changes compared to the lung nodules in Kras(LA1) mice (p<0.05). Early phase imaging using the nanoparticle contrast agent enabled visualization of nodule blood supply. Delayed-phase imaging demonstrated significant differential signal enhancement in the lung nodules of LSL-Kras(G12D);p53(FL/FL) mice compared to nodules in Kras(LA1) mice (p<0.05) indicating higher uptake and accumulation of the nanoparticle contrast agent in rapidly growing nodules.The nanoparticle iodinated contrast agent enabled visualization of blood supply to the nodules during the early-phase imaging. Delayed-phase imaging enabled characterization of slow growing and rapidly growing nodules based on signal enhancement. The use of this agent could facilitate early detection and diagnosis of pulmonary lesions as well as have implications on treatment response and monitoring

    On the maximal spectrum of commutative semiprimitive rings

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    The space of maximal ideals is studied on semiprimitive rings and reduced rings, and the relation between topological properties of Max(R) and algebric properties of the ring R are investigated. The socle of semiprimitive rings is characterized homologically, and it is shown that the socle is a direct sum of its localizations with respect to isolated maximal ideals. We observe that the Goldie dimension of a semiprimitive ring R is equal to the Suslin number of Max(R)

    Flat submodules of free modules over commutative Bezout rings

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    Assessing the dialogic properties of classroom discourse: Proportion models for imbalanced classes

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    Automatic assessment of dialogic properties of classroom discourse would benefit several widespread classroom observation protocols. However, in classrooms with low incidences of dialogic discourse, assessment can be highly biased against detecting dialogic properties. In this paper, we present an approach to addressing this imbalanced class problem. Rather than perform classifications at the utterance level, we aggregate feature vectors to classify proportions of dialogic properties at the class-session level and achieve a moderate correlation with actual proportions, r(130) = .50, p \u3c .001, CI95[.36,.61] . We show that this approach outperforms aggregating utterance level classifications, r(130) = .27, p = .001, CI95[.11,.43], is stable for both low and high dialogic classrooms, and is stable across both automatic speech recognition and human transcripts
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