Fetal heart rate monitoring is the process of checking the condition of the fetus during pregnancy and it would allow doctors and nurses to detect early signs of trouble during labor and delivery. The fetal ECG (FECG) signal is so weak and also is corrupted by other signals and noises, mainly by maternal ECG signal. It is so hard to acquire a noise-free, precise and reliable FECG using the conventional methods. In this study, a combination of empirical mode decomposition (EMD) algorithms, correlation and match filtering is used for extracting FECG from maternal abdominal ECG signals. The proposed method benefits from match filtering ability to detect fetal signal and QRS complex to detect weak QRS peaks. The combined method, has been applied successfully on different signal qualities, even for signals that their analysis was hard and complicated for other methods. This method is able to detect R-R intervals with high accuracy. It was proved that the complete ensemble empirical mode decomposition method provides a better frequency resolution of modes and also requires less iterations that leads to a considerably less computational cost than EMD and ensemble empirical mode decomposition and can reconstruct the FECG completely from the calculated modes. We believe that this method opens a new field in non-invasive maternal abdominal signal processing so the FECG signal could be extracted with high speed and accuracy.

Abstract:In recent years, an increasing number of various surgeries are observed utilizing fluoroscopy. The radiation exposure received by patients and medical staff and the surgical guidance in multiple planes frequently necessitate the positioning of a mobile C-arm. Operative navigation enables a mobile C-arm to provide multiplanar surgical guidance and decreases the radiation dose to the patient and operating room personnel. In this study, we propose a videobased tracked mobile C-arm (referred to as a "tracked C-arm system") to position the system. This system defines a reference framework to maintain the video-optical tracker data and computed tomography (CT) or cone-beam CT images' alignment as fine as possible despite patient or tracker movement. By employing our uniquely designed "sixfacet" reference marker attached to the spine phantom, registration between the video-optical tracker and the spine phantom is maintained at arbitrary angles of the mobile C-arm. The tracked C-arm system provides a statistically significant improvement (P < 0.001) in target registration error in comparison with the conventional system: 0.80 ± 0.34 mm versus 1.60 ± 0.43 mm, respectively. The tracked C-arm system is designed to generate digitally reconstructed radiograph images from the mobile C-arm perspective, with projection error on the order of 0.74 ± 0.13 mm. Integration of the hybrid tracking system with mobile C-arm guidance has the capability to provide registration, reduce radiation exposure, and improve target registration accuracy.

In this work, a new shape based method to improve the accuracy of Brain Ultrasound-MRI image registration is proposed. The method is based on modified Shape Context (SC) descriptor in combination with CPD algorithm. An extensive experiment was carried out to evaluate the robustness of this method against different initialization conditions. As the results prove, the overall performance of the proposed algorithm outperforms both SC and CPD methods. In order to have control over the registration procedure, we simulated the deformations, missing points and outliers according to our Phantom MRI images.

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