Current Issue : July - September Volume : 2019 Issue Number : 3 Articles : 5 Articles
Skull stripping in brain magnetic resonance imaging (MRI) is an essential step to analyze\nimages of the brain. Although manual segmentation has the highest accuracy, it is a time-consuming\ntask. Therefore, various automatic segmentation algorithms of the brain in MRI have been devised\nand proposed previously. However, there is still no method that solves the entire brain extraction\nproblem satisfactorily for diverse datasets in a generic and robust way. To address these shortcomings\nof existing methods, we propose the use of a 3D-UNet for skull stripping in brain MRI. The 3D-UNet\nwas recently proposed and has been widely used for volumetric segmentation in medical images due\nto its outstanding performance. It is an extended version of the previously proposed 2D-UNet, which\nis based on a deep learning network, specifically, the convolutional neural network. We evaluated\n3D-UNet skull-stripping using a publicly available brain MRI dataset and compared the results with\nthree existing methods (BSE, ROBEX, and Kleesiekâ??s method; BSE and ROBEX are two conventional\nmethods, and Kleesiekâ??s method is based on deep learning). The 3D-UNet outperforms two typical\nmethods and shows comparable results with the specific deep learning-based algorithm, exhibiting a\nmean Dice coefficient of 0.9903, a sensitivity of 0.9853, and a specificity of 0.9953....
Objective: Ultrasound (US) and magnetic resonance imaging (MRI) are recommended in the diagnostic process\nof rheumatoid arthritis. Research on its comparability in early disease phases is scarce. Therefore, we compared\nsynovitis and tenosynovitis detected by US and MRI on joint/tendon level.\nMethods: Eight hundred forty joints and 700 tendons of 70 consecutive patients, presenting with inflammatory\narthritis or clinically suspect arthralgia, underwent US and MRI of MCP (2â??5), wrist and MTP (1â??5) joints at the\nsame day. Greyscale (GS) and power Doppler (PD) synovitis were scored according to the modified Szkudlarek\nmethod (combining synovial effusion and hypertrophy) and the recently published EULAR-OMERACT method\n(synovial hypertrophy regardless of the presence of effusion) on static images. US-detected tenosynovitis was\nscored according to the OMERACT. MRI scans were scored according to the RAMRIS. Test characteristics were\ncalculated on joint/tendon level with MRI as reference.................
To build a representation of what we see, the human brain recruits regions throughout the\nvisual cortex in cascading sequence. Recently, an approach was proposed to evaluate the dynamics\nof visual perception in high spatiotemporal resolution at the scale of the whole brain. This method\ncombined functional magnetic resonance imaging (fMRI) data with magnetoencephalography (MEG)\ndata using representational similarity analysis and revealed a hierarchical progression from primary\nvisual cortex through the dorsal and ventral streams. To assess the replicability of this method,\nwe here present the results of a visual recognition neuro-imaging fusion experiment and compare\nthem within and across experimental settings. We evaluated the reliability of this method by\nassessing the consistency of the results under similar test conditions, showing high agreement\nwithin participants. We then generalized these results to a separate group of individuals and visual\ninput by comparing them to the fMRI-MEG fusion data of Cichy et al (2016), revealing a highly\nsimilar temporal progression recruiting both the dorsal and ventral streams. Together these results are\na testament to the reproducibility of the fMRI-MEG fusion approach and allows for the interpretation\nof these spatiotemporal dynamic in a broader context....
Background: This study was performed to assess changes in diffusion tensor imaging (DTI) over time in patients\nwith amyotrophic lateral sclerosis (ALS).\nMethods: We performed DTI in 23 ALS patients who had two magnetic resonance imaging (MRI) scans at 6 month\nintervals and to correlate results with clinical features. The revised ALS functional rating scale (ALSFRSâ??R) was\nadministered at each clinical visit. Data analysis included voxelâ??based white matter tractâ??based spatial statistics\n(TBSS) and atlasâ??based regionâ??ofâ??interest (ROI) analysis of fractional anisotropy (FA) and mean diffusivity (MD).\nResults: With TBSS, there were no significant changes between the two scans. The average change in FA and MD\nin the ROIs over 6 months was small and not significant after allowing for multiple comparisons. After allowing for\nmultiple comparisons, there was no significant correlation of FA or MD with ALSFRSâ??R.\nConclusion: This study shows that there is little evidence of progressive changes in DTI over time in ALS. This\ncould be because white matter is already substantially damaged by the time of onset of symptoms of ALS....
Background: MRI-detected subclinical joint inflammation in the hand joints of patients with undifferentiated\narthritis (UA) predicts progression to rheumatoid arthritis (RA). It is unknown if adding MRI of the foot increases\npredictive accuracy compared to the hand alone.\nMethods: 1.5-T contrast-enhanced MRI of the unilateral foot (MTP-1-5) and hand (MCP-2-5 and wrist) was\nperformed in 123 patients presenting with UA (not fulfilling the 2010 RA criteria) and scored for bone\nmarrow edema (BME), synovitis and tenosynovitis. Symptom-free controls (n = 193) served as a reference for\ndefining an abnormal MRI. Patients were followed for RA development greater than or equal to, defined as fulfilling the\nclassification criteria or initiation of disease-modifying antirheumatic drugs because of the expert opinion of\nRA. The added predictive value of foot MRI to hand MRI was evaluated.\nResults: Fifty-two percent developed RA. Foot tenosynovitis was predictive (OR 2.55, 95% CI 1.01-6.43), independent of\nBME and synovitis (OR 3.29, 95% CI 1.03-10.53), but not independent of CRP and number of swollen joints (OR 2.14, 95%\nCI 0.77-5.95). Hand tenosynovitis was also predictive independent of BME and synovitis (OR 3.99, 95% CI 1.64-9.69) and\nindependent of CRP and swollen joints (OR 2.36, 95% CI 1.04-5.38). Adding foot tenosynovitis to hand tenosynovitis\nchanged the sensitivity from 72 to 73%, specificity from 59 to 54% and AUC from 0.66 to 0.64; the net reclassification\nindex was-3.5.\nConclusion: MRI-detected tenosynovitis of the foot predicts progression to RA. However, adding MRI of the foot does\nnot improve the predictive accuracy compared to MRI of the hand alone. In view of cost reduction, the performance of\nfoot MRI for prognostic purposes in UA can be omitted....
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