Image segmentation

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction
Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed… read more

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction
Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed… read more

BucketAugment: Reinforced Domain Generalisation in Abdominal CT Segmentation
BucketAugment: Reinforced Domain Generalisation in Abdominal CT Segmentation 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Goal: In recent years, deep neural networks have consistently outperformed previously proposed methods in the domain of medical segmentation. However, due to their nature, these networks often struggle to delineate… 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
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