Computer-aided diagnosis and the evaluation of lung disease.
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Humans↗
Biomedical subjects
Jane P Ko
Publications and source records attributed to Jane P Ko.
Segmentation of nodules on chest computed tomography for growth assessment.
Several segmentation methods to evaluate growth of small isolated pulmonary nodules on chest computed tomography (CT) are presented. The segmentation methods are based on adaptively thresholding attenuation levels and use measures of nodule shape. The segmentation methods were first tested on a realistic chest phantom to evaluate their performance with respect to specific nodule characteristics. The segmentation methods were also tested on sequential CT scans of patients. The methods' estimation of nodule growth were compared to the volume change calculated by a chest radiologist. The best method segmented nodules on average 43% smaller or larger than the actual nodule when errors were computed across all nodule variations on the phantom. Some methods achieved smaller errors when examined with respect to certain nodule properties. In particular, on the phantom individual methods segmented solid nodules to within 23% of their actual size and nodules with 60.7 mm3 volumes to within 14%. On the clinical data, none of the methods examined showed a statistically significant difference in growth estimation from the radiologist.
Algorithms↗
Wavelet compression of low-dose chest CT data: effect on lung nodule detection.
PURPOSE: To assess the effect of using a lossy Joint Photographic Experts Group standard for wavelet image compression, JPEG2000, on pulmonary nodule detection at low-dose computed tomography (CT). MATERIALS AND METHODS: One hundred sets of lung CT data ("cases") were compressed to 30:1, 20:1, and 10:1 levels by using a wavelet-based JPEG2000 method, resulting in 400 test cases. Each case consisted of nine 1.25-mm sections that had been obtained with 20-40 mAs. Four thoracic radiologists independently interpreted the test case images. Performance was measured by using area under the receiver operating characteristic (ROC) curve (Az) and conventional sensitivity and specificity analyses. RESULTS: There were 51 cases with and 49 without lung nodules. Az values were 0.984, 0.988, 0.972, 0.921, respectively, for original and 10:1, 20:1, and 30:1 compressed images. Az values decreased significantly at 30:1 (P =.014) but not at 10:1 compression, with a trend toward significant decrease at 20:1 (P =.051). Specificity values were unaffected by compression (>98.0% at all compression levels). Sensitivity values were 86.3% (176 of 204 test cases with nodules), 77.9% (159 of 204 cases), 76.5% (156 of 204 cases), and 70.1% (143 of 204 cases), respectively, for original and 10:1, 20:1, and 30:1 compressed images. Results of logistic regression model analysis confirmed the significant effects of compression rate and nodule attenuation, size, and location on sensitivity (P <.05). CONCLUSION: While no reduction in nodule detection at 10:1 compression levels was demonstrated by using ROC analysis, a significant decrease in sensitivity was identified. Further investigation is needed before widespread use of image compression technology in low-dose chest CT can be recommended.
Humans↗
Lung nodule detection and characterization with multislice CT.
The ability to identify and characterize pulmonary nodules has been dramatically increased by the introduction of multislice CT (MSCT) technology. Using high-resolution sections, MSCT allows considerable improvement in assessing nodule morphology, enhancement patterns, and growth. MSCT also has facilitated the development and potential of clinical application of computer-assisted diagnosis.
Algorithms↗
Landmark detection in the chest and registration of lung surfaces with an application to nodule registration.
We developed an automated system for registering computed tomography (CT) images of the chest temporally. Our system detects anatomical landmarks, in particular, the trachea, sternum and spine, using an attenuation-based template matching approach. It computes the optimal rigid-body transformation that aligns the corresponding landmarks in two CT scans of the same patient. This transformation then provides an initial registration of the lung surfaces segmented from the two scans. The initial surface alignment is refined step by step in an iterative closest-point (ICP) process. To establish the correspondence of lung surface points, Elias' nearest neighbor algorithm was adopted. Our method improves the processing time of the original ICP algorithm from O(kn log n) to O(kn), where k is the number of iterations and n the number of surface points. The surface transformation is applied to align nodules in the initial CT scan with nodules in the follow-up scan. For 56 out of 58 nodules in the initial CT scans of 10 patients, nodule correspondences in the follow-up scans are established correctly. Our methods can therefore potentially facilitate the radiologist's evaluation of pulmonary nodules on chest CT for interval growth.
Algorithms↗
Small pulmonary nodules: volume measurement at chest CT--phantom study.
Three-dimensional methods for quantifying pulmonary nodule volume at computed tomography (CT) and the effect of imaging variables were studied by using a realistic phantom. Two fixed-threshold methods, a partial-volume method (PVM) and a variable method, were used to calculate volumes of 40 plastic nodules (largest dimension, <5 mm: 20 nodules with solid attenuation and 20 with ground-glass attenuation) of known volume. Tube current times (20 and 120 mAs), reconstruction algorithms (high and low frequency), and nodule characteristics were studied. Higher precision was associated with use of a PVM with predetermined pure nodule attenuation, high-frequency algorithm, and diagnostic CT technique (120 mAs). A PVM is promising for volume quantification and follow-up of nodules.
Algorithms↗
Pulmonary aspergillosis in an immunocompetent patient.
SUMMARY: A case of an immunocompetent patient with severe Aspergillus infection and radiographic findings typically described with angioinvasive aspergillosis is presented. When Aspergillus is isolated from the sputum in a patient with normal immunity, invasive aspergillosis should be considered when there are extensive radiographic findings characteristic of invasive fungal disease.
Amphotericin B↗