Current Issue : July - September Volume : 2014 Issue Number : 3 Articles : 6 Articles
Background: Delineation of the target volume is a time-consuming task in radiotherapy treatment planning, yet\r\nessential for a successful treatment of cancers such as prostate cancer. To facilitate the delineation procedure, the\r\npaper proposes an intuitive approach for 3D modeling of the prostate by slice-wise best fitting ellipses.\r\nMethods: The proposed estimate is initialized by the definition of a few control points in a new patient. The method\r\nis not restricted to particular image modalities but assumes a smooth shape with elliptic cross sections of the object.\r\nA training data set of 23 patients was used to calculate a prior shape model. The mean shape model was evaluated\r\nbased on the manual contour of 10 test patients. The patient records of training and test data are based on axial\r\nT1-weighted 3D fast-field echo (FFE) sequences. The manual contours were considered as the reference model.\r\nVolume overlap (Vo), accuracy (Ac) (both ratio, range 0-1, optimal value 1) and Hausdorff distance (HD) (mm, optimal\r\nvalue 0) were calculated as evaluation parameters.\r\nResults: The median and median absolute deviation (MAD) between manual delineation and deformed mean best\r\nfitting ellipses (MBFE) was Vo (0.9 �± 0.02), Ac (0.81 �± 0.03) and HD (4.05 �± 1.3)mm and between manual delineation\r\nand best fitting ellipses (BFE) was Vo (0.96 �± 0.01), Ac (0.92 �± 0.01) and HD (1.6 �± 0.27)mm. Additional results show a\r\nmoderate improvement of the MBFE results after Monte Carlo Markov Chain (MCMC) method.\r\nConclusions: The results emphasize the potential of the proposed method of modeling the prostate by best fitting\r\nellipses. It shows the robustness and reproducibility of the model. A small sample test on 8 patients suggest possible\r\ntime saving using the model...
Background: Functional magnetic resonance imaging (fMRI) analysis is commonly done with cross-correlation\r\nanalysis (CCA) and the General Linear Model (GLM). Both CCA and GLM techniques, however, typically perform\r\ncalculations on a per-voxel basis and do not consider relationships neighboring voxels may have. Clustered voxel\r\nanalyses have then been developed to improve fMRI signal detections by taking advantages of relationships of\r\nneighboring voxels. Mean-shift clustering (MSC) is another technique which takes into account properties of\r\nneighboring voxels and can be considered for enhancing fMRI activation detection.\r\nMethods: This study examines the adoption of MSC to fMRI analysis. MSC was applied to a Statistical Parameter\r\nImage generated with the CCA technique on both simulated and real fMRI data. The MSC technique was then\r\ncompared with CCA and CCA plus cluster analysis. A range of kernel sizes were used to examine how the\r\ntechnique behaves.\r\nResults: Receiver Operating Characteristic curves shows an improvement over CCA and Cluster analysis. False\r\npositive rates are lower with the proposed technique. MSC allows the use of a low intensity threshold and also\r\ndoes not require the use of a cluster size threshold, which improves detection of weak activations and highly\r\nfocused activations.\r\nConclusion: The proposed technique shows improved activation detection for both simulated and real Blood\r\nOxygen Level Dependent fMRI data. More detailed studies are required to further develop the proposed technique....
Background: The European Society of Cardiology recommends that patients with >10% area of ischemia should\r\nreceive revascularization. We investigated inter-observer variability for the extent of ischemic defects reported by\r\ndifferent physicians and by different software tools, and if inter-observer variability was reduced when the physicians\r\nwere provided with a computerized suggestion of the defects.\r\nMethods: Twenty-five myocardial perfusion single photon emission computed tomography (SPECT) patients who were\r\nregarded as ischemic according to the final report were included. Eleven physicians in nuclear medicine delineated the\r\nextent of the ischemic defects. After at least two weeks, they delineated the defects again, and were this time provided\r\na suggestion of the defect delineation by EXINI HeartTM (EXINI). Summed difference scores and ischemic extent values\r\nwere obtained from four software programs.\r\nResults: The median extent values obtained from the 11 physicians varied between 8% and 34%, and between 9% and\r\n16% for the software programs. For all 25 patients, mean extent obtained from EXINI was 17.0% (�± standard deviation\r\n(SD) 14.6%). Mean extent for physicians was 22.6% (�± 15.6%) for the first delineation and 19.1% (�± 14.9%) for the\r\nevaluation where they were provided computerized suggestion. Intra-class correlation (ICC) increased from 0.56\r\n(95% confidence interval (CI) 0.41-0.72) to 0.81 (95% CI 0.71-0.90) between the first and the second delineation,\r\nand SD between physicians were 7.8 (first) and 5.9 (second delineation).\r\nConclusions: There was large variability in the estimated ischemic defect size obtained both from different\r\nphysicians and from different software packages. When the physicians were provided with a suggested delineation,\r\nthe inter-observer variability decreased significantly....
Background: Coccidioidomycosis is an endemic fungal infection in the southwestern of United States. Most\r\ninfections are asymptomatic or manifest with mild respiratory complaints. Rare cases may cause extrapulmonary or\r\ndisseminated disease. We report two cases of knee involvement that presented as isolated lytic lesions of the\r\npatella mimicking neoplasms.\r\nCase Presentation: The first case, a 27 year-old immunocompetent male had progressive left anterior knee pain for\r\nfour months. The second case was a 78 year-old male had left anterior knee pain for three months. Both of them\r\nhad visited general physicians without conclusive diagnosis. A low attenuation lytic lesion in the patella was\r\ndemonstrated on their image studies, and the initial radiologist�s interpretation was suggestive of a primary bony\r\nneoplasm. The patients were referred for orthopaedic oncology consultation. The first case had a past episode of\r\npulmonary coccioidomycosis 2 years prior, while the second case had no previous coccioidal infection history but\r\nlived in an endemic area, the central valley of California. Surgical biopsy was performed in both cases due to\r\ndiagnostic uncertainty. Final pathologic examination revealed large thick walled spherules filled with endospores\r\nestablishing the final diagnosis of extrapulmonary coccidioidomycosis.\r\nConclusions: Though history and laboratory findings are supportive, definitive diagnosis still depends on growth in\r\nculture or endospores identified on histology. We suggest that orthopaedic surgeons and radiologists keep in mind\r\nthat chronic fungal infections can mimic osseous neoplasm by imaging....
Background: To evaluate the inter-study, inter-reader and intra-reader reproducibility of cardiac cine and scar\r\nimaging in rats using a clinical 3.0 Tesla magnetic resonance (MR) system.\r\nMethods: Thirty-three adult rats (Spragueââ?¬â??Dawley) were imaged 24 hours after surgical occlusion of the left\r\nanterior descending coronary artery using a 3.0 Tesla clinical MR scanner (Philips Healthcare, Best, The Netherlands)\r\nequipped with a dedicated 70 mm solenoid receive-only coil. Left-ventricular (LV) volumes, mass, ejection fraction\r\nand amount of myocardial scar tissue were measured. Intra-and inter-observer reproducibility was assessed in all\r\nanimals. In addition, repeat MR exams were performed in 6 randomly chosen rats within 24 hours to assess\r\ninter-study reproducibility.\r\nResults: The MR imaging protocol was successfully completed in 32 (97%) animals. Bland-Altman analysis\r\ndemonstrated high intra-reader reproducibility (mean bias%: LV end-diastolic volume (LVEDV), -1.7%; LV end-systolic\r\nvolume (LVESV), -2.2%; LV ejection fraction (LVEF), 1.0%; LV mass, -2.7%; and scar mass, -1.2%) and high inter-reader\r\nreproducibility (mean bias%: LVEDV, 3.3%; LVESV, 6.2%; LVEF, -4.8%; LV mass, -1.9%; and scar mass, -1.8%). In addition,\r\na high inter-study reproducibility was found (mean bias%: LVEDV, 0.1%; LVESV, -1.8%; LVEF, 1.0%; LV mass, -4.6%;\r\nand scar mass, -6.2%).\r\nConclusions: Cardiac MR imaging of rats yielded highly reproducible measurements of cardiac volumes/function\r\nand myocardial infarct size on a clinical 3.0 Tesla MR scanner system. Consequently, more widely available high field\r\nclinical MR scanners can be employed for small animal imaging of the heart e.g. when aiming at serial assessments\r\nduring therapeutic intervention studies....
Background: Digital image analysis has the potential to address issues surrounding traditional histological\r\ntechniques including a lack of objectivity and high variability, through the application of quantitative analysis. A key\r\ninitial step in image analysis is the identification of regions of interest. A widely applied methodology is that of\r\nsegmentation. This paper proposes the application of image analysis techniques to segment skin tissue with\r\nvarying degrees of histopathological damage. The segmentation of human tissue is challenging as a consequence\r\nof the complexity of the tissue structures and inconsistencies in tissue preparation, hence there is a need for a new\r\nrobust method with the capability to handle the additional challenges materialising from histopathological damage.\r\nMethods: A new algorithm has been developed which combines enhanced colour information, created following\r\na transformation to the L*a*b* colourspace, with general image intensity information. A colour normalisation step is\r\nincluded to enhance the algorithm�s robustness to variations in the lighting and staining of the input images. The\r\nresulting optimised image is subjected to thresholding and the segmentation is fine-tuned using a combination of\r\nmorphological processing and object classification rules. The segmentation algorithm was tested on 40 digital\r\nimages of haematoxylin & eosin (H&E) stained skin biopsies. Accuracy, sensitivity and specificity of the algorithmic\r\nprocedure were assessed through the comparison of the proposed methodology against manual methods.\r\nResults: Experimental results show the proposed fully automated methodology segments the epidermis with a\r\nmean specificity of 97.7%, a mean sensitivity of 89.4% and a mean accuracy of 96.5%. When a simple user\r\ninteraction step is included, the specificity increases to 98.0%, the sensitivity to 91.0% and the accuracy to 96.8%.\r\nThe algorithm segments effectively for different severities of tissue damage.\r\nConclusions: Epidermal segmentation is a crucial first step in a range of applications including melanoma\r\ndetection and the assessment of histopathological damage in skin. The proposed methodology is able to segment\r\nthe epidermis with different levels of histological damage. The basic method framework could be applied to\r\nsegmentation of other epithelial tissues....
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