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FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery
FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: FetSAM represents a cutting-edge deep learning model aimed at revolutionizing fetal head ultrasound segmentation, thereby elevating prenatal diagnostic precision. Methods: Utilizing a comprehensive dataset-the largest to date for fetal… read more

FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery
FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: FetSAM represents a cutting-edge deep learning model aimed at revolutionizing fetal head ultrasound segmentation, thereby elevating prenatal diagnostic precision. Methods: Utilizing a comprehensive dataset-the largest to date for fetal… read more

FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery
FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: FetSAM represents a cutting-edge deep learning model aimed at revolutionizing fetal head ultrasound segmentation, thereby elevating prenatal diagnostic precision. Methods: Utilizing a comprehensive dataset-the largest to date for fetal… read more

FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery
FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: FetSAM represents a cutting-edge deep learning model aimed at revolutionizing fetal head ultrasound segmentation, thereby elevating prenatal diagnostic precision. Methods: Utilizing a comprehensive dataset-the largest to date for fetal… read more

FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery
FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: FetSAM represents a cutting-edge deep learning model aimed at revolutionizing fetal head ultrasound segmentation, thereby elevating prenatal diagnostic precision. Methods: Utilizing a comprehensive dataset-the largest to date for fetal… read more

A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals
A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: Clinical interpretation of an electrocardiogram (ECG) can be detrimentally affected by noise. Removal of the electromyographic (EMG) noise is particularly challenging due to its spectral overlap with the QRS… read more

A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals
A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: Clinical interpretation of an electrocardiogram (ECG) can be detrimentally affected by noise. Removal of the electromyographic (EMG) noise is particularly challenging due to its spectral overlap with the QRS… read more

Targeted Sensitization of Glioblastoma Multiforme Using AAAPT Technology
Targeted Sensitization of Glioblastoma Multiforme Using AAAPT Technology 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Author(s): Megan Mendieta, Naze G. Avci, Raghu Pandurangi, Yasemin M. Akay, Metin Akay Abstract: Glioblastoma Multiforme (GBM) is the most malignant type of all brain tumors. Current GBM treatment options…

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Call for Papers: Special Issue on Functional Recovery and Brain Plasticity
Call for Papers: Special Issue on Functional Recovery and Brain Plasticity 591 443 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Brain plasticity can be defined as the ability of the nervous system to change its activity in response to intrinsic or extrinsic stimuli by reorganizing its structure, functions, or connections.…

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Call for Papers: Special Issues on Weakly-Supervised Deep Learning and its Applications
Call for Papers: Special Issues on Weakly-Supervised Deep Learning and its Applications 500 333 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

To address biomedical data analysis tasks by learning from noisy, limited, or imprecise expert annotations, researchers have recently started to develop weakly-supervised deep learning (WSDL) techniques, which are of great…

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