The femora of five intact cadaver ovine limbs were scanned using a 1.5 T MRI and a CT scanner. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Eventually, a qualitative edge evaluation is given on a MRI volume of the shoulder joint. Secondly, we use the Pratt's Figure of Merit (FOM) method to evaluate edges preservation. Firstly, the efficiency of the model in the noise reduction is quantified using an entropy criterion on synthetic data with different noise levels to evaluate the smoothing of the regions. So a robust local estimation method is proposed to better eliminate the noise in the image while preserving edges. This process also depends on a threshold gradient parameter which splits both former classes. These values are divided into two classes: high gradients for pixels belonging to edges or noisy pixels, low ones otherwise. The anisotropic diffusion equation is mainly controlled using an automatic edge stopping function based on Tukey's biweight function, which depends on the values of gradients pixels.
We show that smoothing, while preserving edges, helps the segmentation of upper limb bones (shoulder) in MRI data bases. In this work we propose to use an anisotropic diffusion process using robust statistics. This study demonstrates a high accuracy for both CT and MRI imaging, supporting the feasibility of using MRI technology for the 3D reconstruction of bones in medical applications. Different regions of the bones were analysed, indicating a difference in accuracy between diaphysis and epiphysis. MR imaging resulted in an RMS error of 0.56mm however, the MRI bone model was on average a small underestimation of the cleaned bone. The 3D reconstruction using CT images resulted in an RMS error of 0.55mm, corresponding to an overestimated CT bone model compared to the cleaned bone. 3D models of the tibia were created from the segmented CT and MRI images and compared to optical scans of the cleaned bones (considered as ground truth). Clinical CT and MRI scans were acquired from nine lower leg cadavers and the bones were subsequently cleaned from soft tissues. The aim of this study was to quantify the absolute dimensional errors between models reconstructed from computed tomography and magnetic resonance images compared to a ground truth for various regions of the bone. The use of three-dimensional imaging methodologies in new applications in the orthopaedic field has introduced a need for high accuracy, in addition to a correct diagnosis. T1-weighted Silent Scan is a promising technique for acoustic noise reduction and improved patient comfort. The patients' subjective sound level score was lower for Silenz compared with conventional sequence (1.1 vs.
No significant difference was observed between Silenz sound levels and ambient sounds (i.e., background noise in the scanner room, 68.8 dB vs. 104.65 dB with BRAVO, P = 0.024) corresponding to 34.3% reduction in sound intensity and 99,97% reduction in sound pressure. Measured mean noise was reduced significantly with Silenz sequence (68.8 dB vs. Readers rated image quality as fully diagnostic in all patients. Image quality was subjectively assessed in consensus by two radiologists on a 3-point scale. Objective sound level measurements were performed with a dedicated device in gantry at different operation modes. Patients rated subjective sound impression for both sequences on a 6-point scale. T1-weighted gradient echo (BRAVO) and Silenz pulse sequence (TE=0, 3D radial center-out k-space filling and data sampling with relatively small gradient steps) were performed. MATERIALS AND METHODS:Ten patients underwent routine brain MRI with 3 Tesla MR750w system and 12-channel head coil. Here, we report our preliminary experience with this technique in neuroimaging with regard to subjective and objective noise levels and image quality. Silent Scan technology uses less changes in gradient excitation levels, which is directly related to noise levels. Acoustic noise during magnetic resonance imaging (MRI) is the main source for patient discomfort and leads to verbal communication problems, difficulties in sedation, and hearing impairment.
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