&lt;title&gt;Producing lesions for hybrid mammograms: extracted tumors and simulated microcalcifications&lt;/title&gt;

Burgess, Arthur E.; Chakraborty, Samrat

doi:10.1117/12.349659

Cited by 15 publications

(14 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For each image processing, 100 hybrid abnormal images 47,48 were created by superposing 1-3 (average 1.4; 69 images had 1 lesion, 20 images had 2 lesions, and 11 had 3 lesions) simulated clusters of microcalcifications on the raw normal mammograms; the remaining 100 images were the true normal images. The 1000 images (200 × 5) were interpreted under the FROC method by four radiologists, three with more than 15 years' experience and one resident in his last year.…”

Section: Iia Froc and Roc Observer Performance Studiesmentioning

confidence: 99%

“…The data were a subset of a larger study 46 in which 200 cranio-caudal mammograms were processed with five clinical image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OpView v2, Siemens OpView v1). For each image processing, 100 hybrid abnormal images 47,48 were created by superposing 1-3 (average 1.4; 69 images had 1 lesion, 20 images had 2 lesions, and 11 had 3 lesions) simulated clusters of microcalcifications on the raw normal mammograms; the remaining 100 images were the true normal images. The 1000 images (200 × 5) were interpreted under the FROC method by four radiologists, three with more than 15 years' experience and one resident in his last year.…”

Section: Iia Froc and Roc Observer Performance Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Correlation of free‐response and receiver‐operating‐characteristic area‐under‐the‐curve estimates: Results from independently conducted FROC/ROC studies in mammography

et al. 2012

View full text Add to dashboard Cite

show abstract

Section: Iia Froc and Roc Observer Performance Studiesmentioning

confidence: 99%

Section: Iia Froc and Roc Observer Performance Studiesmentioning

confidence: 99%

Correlation of free‐response and receiver‐operating‐characteristic area‐under‐the‐curve estimates: Results from independently conducted FROC/ROC studies in mammography

et al. 2012

View full text Add to dashboard Cite

show abstract

“…We then estimated the background in the vicinity of the tumor and subtracted it to obtain a digital image of the isolated tumor. The background was estimated using a quadratic sur-face method 47 as follows. A 3ϫ3 square grid of points was centered on the lesion with the midpoints of the grid edges close to, but not overlapping, the nearest lesion point.…”

Section: A Materialsmentioning

confidence: 99%

Human observer detection experiments with mammograms and power‐law noise

2001

Self Cite

View full text Add to dashboard Cite

We determined contrast thresholds for lesion detection as a function of lesion size in both mammograms and filtered noise backgrounds with the same average power spectrum, P(f)=B/f3. Experiments were done using hybrid images with digital images of tumors added to digitized normal backgrounds, displayed on a monochrome monitor. Four tumors were extracted from digitized specimen radiographs. The lesion sizes were varied by digital rescaling to cover the range from 0.5 to 16 mm. Amplitudes were varied to determine the value required for 92% correct detection in two-alternative forced-choice (2AFC) and 90% for search experiments. Three observers participated, two physicists and a radiologist. The 2AFC mammographic results demonstrated a novel contrast-detail (CD) diagram with threshold amplitudes that increased steadily (with slope of 0.3) with increasing size for lesions larger than 1 mm. The slopes for prewhitening model observers were about 0.4. Human efficiency relative to these models was as high as 90%. The CD diagram slopes for the 2AFC experiments with filtered noise were 0.44 for humans and 0.5 for models. Human efficiency relative to the ideal observer was about 40%. The difference in efficiencies for the two types of backgrounds indicates that breast structure cannot be considered to be pure random noise for 2AFC experiments. Instead, 2AFC human detection with mammographic backgrounds is limited by a combination of noise and deterministic masking effects. The search experiments also gave thresholds that increased with lesion size. However, there was no difference in human results for mammographic and filtered noise backgrounds, suggesting that breast structure can be considered to be pure random noise for this task. Our conclusion is that, in spite of the fact that mammographic backgrounds have nonstationary statistics, models based on statistical decision theory can still be applied successfully to estimate human performance.

show abstract

“…18,19 All spiculated lesions were simulated using a stochastic growth method. 17 Background and lesion materials were chosen to be Polyethylene and PMMA, which were considered as the surrogate materials for adipose tissue and glandular tissue, respectively. Phase and absorption properties of the two materials were taken from NIST and are listed in Table 3.…”

Section: Application Of the Framework To A Dedicated Breast Ct Systemmentioning

confidence: 99%

How to determine detection performance of a DPC-CT system from a conventional cone beam CT system?

Garrett

Bevins

et al. 2013

Medical Imaging 2013: Physics of Medical Imaging

View full text Add to dashboard Cite

Although the relative ease of implementation and compact nature of grating-based differential phase contrast CT (DPC-CT) has sparked tremendous enthusiasm for potential medical applications, the pros and cons of this imaging method remains to be addressed before an actual clinical system can be constructed. To address these unknowns, either numerical simulations or direct hardware implementations can be used. However, both approaches have their limitations. It is highly desirable to develop a research method to enable imaging performance prediction for a future DPC-CT system from the performance of an available absorption CT (ACT) system. In this paper, a theoretical framework was developed to accurately predict the noise properties and detection performance of DPC-CT from that of conventional ACT. The framework was derived based on a fundamental noise relationship between DPC-CT and ACT and was experimentally validated. An example has been given in the paper on how the framework can be utilized to predict model observer detectability index of a DPC breast CT constructed based on an existing absorption breast CT. This framework is expected to become a valuable tool in addressing the following questions: (i) With a fixed radiation dose in a particular clinical application, how well can a specific detection/discrimination imaging task can be performed provided that an existing ACT scanner is modified into a DPC-CT by inserting a grating interferometer, which is characterized by a few design parameters (e.g., pitches and duty cycles of the gratings, relative distance between the gratings, etc.) into the ACT system? (ii) If a DPC-CT system can outperform an ACT for certain detection/discrimination tasks under the constraint of identical radiation dose to the image object, how would one optimize design parameters of the gratings in order to maximize its potential clinical benefits?

show abstract

<title>Producing lesions for hybrid mammograms: extracted tumors and simulated microcalcifications</title>

Cited by 15 publications

References 1 publication

Correlation of free‐response and receiver‐operating‐characteristic area‐under‐the‐curve estimates: Results from independently conducted FROC/ROC studies in mammography

Correlation of free‐response and receiver‐operating‐characteristic area‐under‐the‐curve estimates: Results from independently conducted FROC/ROC studies in mammography

Human observer detection experiments with mammograms and power‐law noise

How to determine detection performance of a DPC-CT system from a conventional cone beam CT system?

Contact Info

Product

Resources

About