In this work, we have developed and evaluated an electrocardiogram (ECG) feature extraction system based on the multi-resolution wavelet transform. ECG signals from Modified Lead II (MLII) are chosen for processing. The result of applying two wavelet filters (D4 and D6) of different length on the signal is compared. The wavelet filter with scaling function more closely to the shape of the ECG signal achieved better detection. In the first step, the ECG signal was de-noised by removing the corresponding wavelet coefficients at higher scales. Then, QRS complexes are detected and each complex is used to locate the peaks of the individual waves, including onsets and offsets of the P and T waves which are present in one cardiac cycle. We evaluated the algorithm on MIT-BIH Database, the manually annotated database, for validation purposes. The proposed QRS detector achieved sensitivity of 75. 2 % 18 . 99 .. and a positive predictivity of 45 . 4 % 00 . 98 .. over the validation database.

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Multimodality image registration plays a crucial role in various clinical and research applications. The aim of this study is to present an optimized MR to CT whole‐body deformable image registration algorithm and its validation using clinical studies. A 3D intermodality registration technique based on B‐spline transformation was performed using optimized parameters of the elastix package based on the Insight Toolkit (ITK) framework. Twenty‐eight (17 male and 11 female) clinical studies were used in this work. The registration was evaluated using anatomical landmarks and segmented organs. In addition to 16 anatomical landmarks, three key organs (brain, lungs, and kidneys) and the entire body volume were segmented for evaluation. Several parameters — such as the Euclidean distance between anatomical landmarks, target overlap, Dice and Jaccard coefficients, false positives and false negatives, volume similarity, distance error, and Hausdorff distance — were calculated to quantify the quality of the registration algorithm. Dice coefficients for the majority of patients (>75%) were in the 0.8–1 range for the whole body, brain, and lungs, which satisfies the criteria to achieve excellent alignment. On the other hand, for kidneys, Dice coefficients for volumes of 25% of the patients meet excellent volume agreement requirement, while the majority of patients satisfy good agreement criteria (>0.6). For all patients, the distance error was in 0–10 mm range for all segmented organs. In summary, we optimized and evaluated the accuracy of an MR to CT deformable registration algorithm. The registered images constitute a useful 3D whole‐body MR‐CT atlas suitable for the development and evaluation of novel MR‐guided attenuation correction procedures on hybrid PET‐MR systems.PACS number: 07.05.Pj

The proposed projected surface imaging in conjunction with the Doppler US data combined in a powerful biomechanical model can result an acceptable performance in calculation of deformation during surgical navigation. However, the projected landmark method is sensitive to ambient light and surface conditions and the Doppler ultrasound suffers from noise and 3D image construction problems, the combination of these two methods applied on a FEM has an eligible performance.