One of the most important problems in the segmentation of lung nodules in CT imaging arises from possible attachments occurring between nodules and other lung structures, such as vessels or pleura. In this report, we address the problem of vessels attachments by proposing an automated correction method applied to an initial rough segmentation of the lung nodule. The method is based on a local shape analysis of the initial segmentation making use of 3-D geodesic distance map representations. The correction method has the advantage that it locally refines the nodule segmentation along recognized vessel attachments only, without modifying the nodule boundary elsewhere. The method was tested using a simple initial rough segmentation, obtained by a fixed image thresholding. The validation of the complete segmentation algorithm was carried out on small lung nodules, identified in the ITALUNG screening trial and on small nodules of the lung image database consortium (LIDC) dataset. In fully automated mode, 217/256 (84.8%) lung nodules of ITALUNG and 139/157 (88.5%) individual marks of lung nodules of LIDC were correctly outlined and an excellent reproducibility was also observed. By using an additional interactive mode, based on a controlled manual interaction, 233/256 (91.0%) lung nodules of ITALUNG and 144/157 (91.7%) individual marks of lung nodules of LIDC were overall correctly segmented. The proposed correction method could also be usefully applied to any existent nodule segmentation algorithm for improving the segmentation quality of juxta-vascular nodules.

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Lung densitometry assesses with computed tomography (CT) the X-ray attenuation of the pulmonary tissue which reflects both the degree of inflation and the structural lung abnormalities implying decreased attenuation, as in emphysema and cystic diseases, or increased attenuation, as in fibrosis. and with pulmonary fibrosis. It has also been applied to assess prevalence of smoking-related emphysema and to monitor progression of smoking-related emphysema, alpha1 antitrypsin deficiency emphysema, and pulmonary fibrosis. Finally, it is recommended as end-point in pharmacological trials of emphysema and lung fibrosis.

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The presence of brain atrophy and its progression in early Parkinson's disease (PD) are still a matter of debate, particularly in patients without cognitive impairment. The aim of this longitudinal study was to assess whether PD patients who remain cognitively intact develop progressive atrophic changes in the early stages of the disease. For this purpose, we employed high-resolution T1-weighted MR imaging to compare 22 drug-naïve de novo PD patients without cognitive impairment to 17 age-matched control subjects, both at baseline and at three-year follow-up. We used tensor-based morphometry to explore the presence of atrophic changes at baseline and to compute yearly atrophy rates, after which we performed voxel-wise group comparisons using threshold-free cluster enhancement. At baseline, we did not observe significant differences in regional atrophy in PD patients with respect to control subjects. In contrast, PD patients showed significantly higher yearly atrophy rates in the prefrontal cortex, anterior cingulum, caudate nucleus, and thalamus when compared to control subjects. Our results indicate that even cognitively preserved PD patients show progressive cortical and subcortical atrophic changes in regions related to cognitive functions and that these changes are already detectable in the early stages of the disease.

Abstract-Computed tomography (CT) is the most sensitive imaging technique for detecting lung nodules, and is now being evaluated as a screening tool for lung cancer in several large samples studies all over the world. In this report, we describe a semiautomatic method for 3-D segmentation of lung nodules in CT images for subsequent volume assessment. The distinguishing features of our algorithm are the following. 1) The user interaction process. It allows the introduction of the knowledge of the expert in a simple and reproducible manner. 2) The adoption of the geodesic distance in a multithreshold image representation. It allows the definition of a fusion-segregation process based on both gray-level similarity and objects shape. The algorithm was validated on low-dose CT scans of small nodule phantoms (mean diameter 5.3-11 mm) and in vivo lung nodules (mean diameter 5-9.8 mm) detected in the Italung-CT screening program for lung cancer. A further test on small lung nodules of Lung Image Database Consortium (LIDC) first data set was also performed. We observed a RMS error less than 6.6% in phantoms, and the correct outlining of the nodule contour was obtained in 82/95 lung nodules of Italung-CT and in 10/12 lung nodules of LIDC first data set. The achieved results support the use of the proposed algorithm for volume measurements of lung nodules examined with low-dose CT scanning technique.Index Terms-Computer-aided diagnosis, computer vision, lung cancer, lung nodules segmentation, medical imaging, multiscale processing, spiral computed tomography (CT).

The selective decrease of FA in SCPs of FRDA patients reflecting chronic WM tract damage is associated with increase of both the axial and radial diffusivity, the latter more pronounced than the former. The ultrastructural and biophysical bases of the increased axial diffusivity in chronically degenerating WM tracts deserve further studies.

We compared whole-lung densitometry with visual evaluation of pulmonary emphysema. Thirty patients with chronic obstructive pulmonary disease underwent multi-detector CT (150 mAs and 0.75 collimation) with double reconstruction: thick (5-mm) slices with smooth filter for whole-lung densitometry and thin (1 mm) slices with sharp filter for visual assessment (one of every ten slices). Densitometry and visual assessment were performed by three operators each, and the time required for assessment, the inter-observer agreement and the correlation with the results of the diffusion capacity of carbon monoxide (DL(CO)) in the same patients were computed. The average time for densitometry (8.49 +/- 0.13 min) was significantly longer (p < 0.0001) than that for visual evaluation (5.14 +/- 0.11 min). However, the inter-operator agreement ranged between "moderate" to "almost perfect" for densitometry (kappa range 0.58-0.87) and "slight" for visual (kappa = 0.20) assessment. The correlation coefficients of DL(CO) with relative area at -960 and -970 Hounsfield units (HU) (both r = -0.66) and of the first percentile point of lung density (r = 0.66) were slightly stronger than that of the visual score (r = -0.62). Densitometry should be preferred to visual assessment because it enables a more reproducible evaluation of the extent of pulmonary emphysema, which can be carried out on the entire lung in a reasonable amount of time.