To compare three different reconstruction techniques of CT data for the detection of pulmonary nodules in children under 13 years. Secondly to assess the prevalence of perifissural nodular opacities. The study consisted of chest CTs of 31 children (median age 6.9 years, range 2.1-12.7), of whom 17 had known extra-thoracic malignancies. Four observers assessed three techniques for the presence of nodules: axial 5 mm maximum intensity projections (MIPs) used in conjunction with 1 mm slices (mode A), 1 mm slices alone (mode B) and 3 mm slices (mode C). All modes were available in 3D. Per mode sensitivities were determined above a certain threshold of reader agreement. Confidence level and reader agreement for identification of an opacity as no...
To compare human observers to a mathematically derived computer model for differentiation between ma...
Purpose: To test ultra-low-dose computed tomography (ULDCT) scanning protocols for the detection of ...
PURPOSE To explore the characteristics that impact lung nodule detection by peripheral vision whe...
Background: Maximum intensity projection (MIP) CT image reconstruction is a beneficial diagnostic to...
AbstractBackgroundMaximum intensity projection (MIP) CT image reconstruction is a beneficial diagnos...
Background: Normative data on pulmonary nodules in children without malignancy are limited. Knowledg...
A methodology is presented to detect pulmonary nodules in images reconstructed from low-dose Compute...
OBJECTIVE. the purpose of this article is to assess the feasibility and utility of PET/CT in disting...
Purpose: To study interreader variability for classifying pulmonary opacities at CT as perifissural ...
Contains fulltext : 96753.pdf (Publisher’s version ) (Closed access)RATIONALE AND ...
OBJECTIVE: The objective of this study was to evaluate the detection rates of pulmonary nodules on C...
Purpose: To compare human observers to a mathematically derived computer model for differentiation b...
International audienceThis study aimed at evaluating the diagnostic benefits of maximum intensity pr...
OBJECTIVE: To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmo...
OBJECTIVE: The purpose of this study is to evaluate observer detection and volume measurement of sma...
To compare human observers to a mathematically derived computer model for differentiation between ma...
Purpose: To test ultra-low-dose computed tomography (ULDCT) scanning protocols for the detection of ...
PURPOSE To explore the characteristics that impact lung nodule detection by peripheral vision whe...
Background: Maximum intensity projection (MIP) CT image reconstruction is a beneficial diagnostic to...
AbstractBackgroundMaximum intensity projection (MIP) CT image reconstruction is a beneficial diagnos...
Background: Normative data on pulmonary nodules in children without malignancy are limited. Knowledg...
A methodology is presented to detect pulmonary nodules in images reconstructed from low-dose Compute...
OBJECTIVE. the purpose of this article is to assess the feasibility and utility of PET/CT in disting...
Purpose: To study interreader variability for classifying pulmonary opacities at CT as perifissural ...
Contains fulltext : 96753.pdf (Publisher’s version ) (Closed access)RATIONALE AND ...
OBJECTIVE: The objective of this study was to evaluate the detection rates of pulmonary nodules on C...
Purpose: To compare human observers to a mathematically derived computer model for differentiation b...
International audienceThis study aimed at evaluating the diagnostic benefits of maximum intensity pr...
OBJECTIVE: To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmo...
OBJECTIVE: The purpose of this study is to evaluate observer detection and volume measurement of sma...
To compare human observers to a mathematically derived computer model for differentiation between ma...
Purpose: To test ultra-low-dose computed tomography (ULDCT) scanning protocols for the detection of ...
PURPOSE To explore the characteristics that impact lung nodule detection by peripheral vision whe...