Task-based lens design with application to digital mammography

Chen, Liying; Barrett, Harrison H.

doi:10.1364/josaa.22.000148

Cited by 14 publications

(7 citation statements)

References 38 publications

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“…Consequently, a random value in the interval (−2 o , +2 o ) has been considered as the conservative noise estimate in the phase measurements. Mathematically, this noise can be described by (14) where ζ is a uniformly distributed random number in [0, 1]. The noise, n θ , is added to the phase of detected light, which is a mixture of both emission and excitation photon density waves, to obtain the noisy estimate of phase measurements.…”

Section: Noise-in Optical Imaging Systems Two Main Types Of Fundamenmentioning

confidence: 99%

“…The Hotelling observer's signal-to-noise ratio (SNR Hot ) is a measure of the task performance and has been widely used to evaluate the imaging hardware for tumor detection task in imaging modalities such as PET [9,10], SPECT [11,12], digital mammography [13,14], and optical coherence tomography [15]. Evaluation of imaging system for target detection tasks using the Hotelling observer requires a large number of imaging data sets and, thus, is not easily performed using patient image or experimentally obtained phantom data.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of a fluorescence-enhanced optical imaging system using the Hotelling observer

Sahu¹,

Joshi²,

Kupinski³

et al. 2006

Opt. Express

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This study represents a first attempt to assess the detection capability of a fluorescence-enhanced optical imaging system as quantified by the Hotelling observer. The imaging system is simulated by the diffusion approximation of the time-dependent radiative transfer equation, which describes near infra-red (NIR) light propagation through a breast phantom of clinically relevant volume. Random structures in the background are introduced using a lumpy-object model as a representation of anatomical structure as well as non-uniform distribution of disease markers. The systematic errors and noise associated with the actual experimental conditions are incorporated into the simulated boundary measurements to acquire imaging data sets. A large number of imaging data sets is considered in order to perform Hotelling observer studies. We find that the signal-to-noise ratio (SNR) of Hotelling observer (i) decreases as the strength of lumpy perturbations in the background increases, (ii) decreases as the target depth increases, and (iii) increases as excitation light leakage decreases, and reaches a maximum for filter optical density values of 5 or higher.

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Section: Noise-in Optical Imaging Systems Two Main Types Of Fundamenmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of a fluorescence-enhanced optical imaging system using the Hotelling observer

Sahu¹,

Joshi²,

Kupinski³

et al. 2006

Opt. Express

View full text Add to dashboard Cite

show abstract

“…These models aim at avoiding the subjective and time-consuming aspect of the psychophysical studies, as well as evaluating medical image quality 7,8 . Models for objects superimposed on various types of real backgrounds or computer generated noises have been developed and applied to the detection of lesions in radiological images 9,10,11 .…”

Section: Introductionmentioning

confidence: 99%

“…However, the complexity and computational cost associated with such modeling and the difficulty of taking into account breast compression often takes from the quality of the resulting images. For that reason, 2D approaches have been investigated, using backgrounds constituted by the summation of elementary bright structures called blobs 7,8,13,14 . These lumpy backgrounds, as named originally by Rolland and Barrett 13 , were designed to reproduce the textures observed in mammograms.…”

Section: Introductionmentioning

confidence: 99%

Mammographic texture synthesis using genetic programming and clustered lumpy background

Castella¹,

Kinkel

Descombes³

et al. 2006

SPIE Proceedings

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In this work we investigated the digital synthesis of images which mimic real textures observed in mammograms. Such images could be produced in an unlimited number with tunable statistical properties in order to study human performance and model observer performance in perception experiments. We used the previously developed clustered lumpy background (CLB) technique and optimized its parameters with a genetic algorithm (GA). In order to maximize the realism of the textures, we combined the GA objective approach with psychophysical experiments involving the judgments of radiologists. Thirty-six statistical features were computed and averaged, over 1000 real mammograms regions of interest. The same features were measured for the synthetic textures, and the Mahalanobis distance was used to quantify the similarity of the features between the real and synthetic textures. The similarity, as measured by the Mahalanobis distance, was used as GA fitness function for evolving the free CLB parameters. In the psychophysical approach, experienced radiologists were asked to qualify the realism of synthetic images by considering typical structures that are expected to be found on real mammograms: glandular and fatty areas, and fiber crossings. Results show that CLB images found via optimization with GA are significantly closer to real mammograms than previously published images. Moreover, the psychophysical experiments confirm that all the above mentioned structures are reproduced well on the generated images. This means that we can generate an arbitrary large database of textures mimicking mammograms with traceable statistical properties.

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“…However, the image quality was deeply affected by the artifacts (white dots), which resulted from the noise and the scatter in the projection images. So, more research would be needed to improve the quality of the images [18][19][20][21][22]. 4.…”

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confidence: 99%

Comparison of two detector systems for cone beam CT small animal imaging: a preliminary study

et al. 2006

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PurposeTo compare two detector systems -one based on the charge-coupled device (CCD) and image amplifier, the other based on a-Si/CsI flat panel, for cone beam computed-tomography (CT) imaging of small animals.A high resolution, high framing rate detector system for the cone beam CT imaging of small animals was developed. The system consists of a 2048×3072×12 bit CCD optically coupled to an image amplifier and an x-ray phosphor screen. The CCD has an intrinsic pixel size of 12 μm but the effective pixel size can be adjusted through the magnification adjustment of the optical coupling systems. The system is used in conjunction with an x-ray source and a rotating stage for holding and rotating the scanned object in the cone beam CT imaging experiments. The advantages of the system include but are not limited to the ability to adjust the effective pixel size and to achieve extremely high spatial resolution and temporal resolution. However, the need to use optical coupling compromises the detective quanta efficiency (DQE) of the system. In this paper, the imaging characteristics of the system were presented and compared with those of an a-Si/CsI flat-panel detector system.

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Task-based lens design with application to digital mammography

Cited by 14 publications

References 38 publications

Assessment of a fluorescence-enhanced optical imaging system using the Hotelling observer

Assessment of a fluorescence-enhanced optical imaging system using the Hotelling observer

Mammographic texture synthesis using genetic programming and clustered lumpy background

Comparison of two detector systems for cone beam CT small animal imaging: a preliminary study

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