Reconstruction filters and contrast detail curves in CT

Huda, Walter; Ogden, Kent M.; Samei, Ehsan; Scalzetti, Ernest M.; Lavallee, R. L.; Roskopf, M; Groat, G

doi:10.1117/12.770530

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…Many low-radiation dose protocols have been developed, although most of them also lead to reduced image quality and conspicuity [32,33]. Such protocols are particularly useful in patients <40 years or in conditions in which fine detail is not needed, such as in nephrolithiasis.…”

Section: ) Avoiding Unnecessary Irradiation Of Patientsmentioning

confidence: 99%

Reasons for inadequate or incomplete imaging techniques

Caraiani

Rudd

et al. 2018

Med Ultrason

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Even if imaging has developed considerably during the last decades there still exist several factors which limit its capacities. These factors can either limit the usage of a technique or degrade images making them difficult to interpret. Magnetic resonance imaging (MRI) has, as an absolute contraindication, the presence of metallic devices marked as “MRI unsafe” and metallic foreign bodies close to the eye or vital structures. Claustrophobia and artefacts reduce the application and performance of MRI in a significant proportion of patients. The major disadvantages of computed tomography(CT) are the exposure to ionizing radiation inducing malignancies especially in pediatric patients and the risk of contrast induced allergies and nephropathy. Ultrasound is a safe, easily available and low-cost imaging technique without significant side effects for the patient. Obesity or bloating can severely limit ultrasound capacities.This paper written by radiologists and clinicians, highlights the main reasons leading to inadequate imaging and points out solutions to avoid inaccurate diagnosis due to incomplete imaging or presence of artifacts.

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Section: ) Avoiding Unnecessary Irradiation Of Patientsmentioning

confidence: 99%

Reasons for inadequate or incomplete imaging techniques

Caraiani

Rudd

et al. 2018

Med Ultrason

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“…Most research work on low contrast detection in CT has focused on the use of uniform phantoms and/or the use of anthropomorphic phantoms (3,4). To date, very little work has been performed to investigate low contrast lesion detection in clinical CT images.…”

Section: Introductionmentioning

confidence: 98%

Contrast detail curves in head CT examinations

et al. 2009

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The purpose of this study was to generate contrast detail (CD) curves for low contrast mass lesions embedded in images obtained in head and neck CT examinations. Axial head and neck CT slice images were randomly chosen from patients at five different levels. All images were acquired at 120 kV, and reconstructed using a standard soft tissue reconstruction filter. For each head CT image, we measured detection of low contrast mass lesions using a 2 Alternate Forced Choice (2-AFC) experimental paradigm. In an AFC experiment, an observer identifies the lesion location in one of two regions of interest. After performing 128 sequential observations, it is possible to compute the lesion contrast corresponding to a 92% accuracy of lesion detection (i.e., I 92% ). Five lesion sizes were investigated ranging from 4 mm to 12.5 mm, with the experimental order randomized to eliminate learning curve as well as observer fatigue. Contrast detail curves were generated by plotting log[I 92% ] versus log[lesion size]. Experimental slopes ranged from ~ -0.1 to ~ -0.4. The slope of the CD curve was directly related to the complexity of the anatomical structure in the head CT image. As the apparent anatomical complexity increased, the slope of the corresponding CD curve was reduced. Results from our pilot study suggest that anatomical structure is of greater importance than quantum mottle, and that the type of anatomical background structure is an important determinant of lesion detection in CT imaging.

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“…In the assessment of soft tissues or organs with lower contrast of internal structures, the soft tissue reconstruction (“soft kernel” algorithm) is employed, which reduces noise at the expense of lowering the spatial resolution. Owing to the application of various reconstruction filters, adjustment of the image for further analyses is possible [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Classification Results Accuracy for CT Soft Tissue and Bone Reconstructions in Detecting the Porosity of a Spongy Tissue

Dzierżak

Omiotek

Tkacz

et al. 2022

JCM

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The aim of the study was to compare the accuracy of the classification pertaining to the results of two types of soft tissue and bone reconstructions of the spinal CT in detecting the porosity of L1 vertebral body spongy tissue. The dataset for each type of reconstruction (high-resolution bone reconstruction and soft tissue reconstruction) included 400 sponge tissue images from 50 healthy patients and 50 patients with osteoporosis. Texture feature descriptors were calculated based on the statistical analysis of the grey image histogram, autoregression model, and wavelet transform. The data dimensional reduction was applied by feature selection using nine methods representing various approaches (filter, wrapper, and embedded methods). Eleven methods were used to build the classifier models. In the learning process, hyperparametric optimization based on the grid search method was applied. On this basis, the most effective model and the optimal subset of features for each selection method used were determined. In the case of bone reconstruction images, four models achieved a maximum accuracy of 92%, one of which had the highest sensitivity of 95%, with a specificity of 89%. For soft tissue reconstruction images, five models achieved the highest testing accuracy of 95%, whereas the other quality indices (TPR and TNR) were also equal to 95%. The research showed that the images derived from soft tissue reconstruction allow for obtaining more accurate values of texture parameters, which increases the accuracy of the classification and offers better possibilities for diagnosing osteoporosis.

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Reconstruction filters and contrast detail curves in CT

Cited by 6 publications

References 4 publications

Reasons for inadequate or incomplete imaging techniques

Reasons for inadequate or incomplete imaging techniques

Contrast detail curves in head CT examinations

Comparison of the Classification Results Accuracy for CT Soft Tissue and Bone Reconstructions in Detecting the Porosity of a Spongy Tissue

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