Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 30, 2025
Brain regional segmentation is an image-processing approach widely used in brain image analyses. Deep learning models that perform segmentation alone play an important role in medical fields such as automatic diagnosis and prognosis prediction. This ...
Acquiring high-resolution (HR) MR images of infant brains is challenging due to lengthy scan times and limited subject compliance. Image super-resolution (SR) techniques can generate HR images from low-resolution (LR) inputs, reducing the need for ex...
Many invertebrates voluntarily lose (autotomize) limbs during antagonistic encounters, and some regenerate functional replacements. Because limb loss can have severe consequences on individual fitness, it is likely subject to significant selective pr...
BACKGROUND: Preoperative diagnosis of muscle invasion and American Joint Committee on Cancer (AJCC) stage plays a crucial role in guiding treatment strategies for bladder cancer (BCa). Utilizing quantitative analysis of tumor subregions via CT imagin...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
May 7, 2025
Ultrasound (US) is considered a key modality for the clinical assessment of hepatic steatosis (i.e., fatty liver) due to its noninvasiveness and availability. Deep learning methods have attracted considerable interest in this field, as they are capab...
Neural networks : the official journal of the International Neural Network Society
May 6, 2025
In Unsupervised Domain Adaptation Semantic Segmentation (UDASS), while self-training techniques have become one of the most effective methods to date, the absence of target labels makes models susceptible to overfitting. To address this problem, cons...
IEEE journal of biomedical and health informatics
May 6, 2025
Robust decoding performance is essential for the practical deployment of brain-computer interface (BCI) systems. Existing EEG decoding models often rely on large amounts of annotated data collected through specific experimental setups, which fail to ...
Cardiac motion estimation is important for assessing the contractile health of the heart, and performing this in 3D can provide advantages due to the complex 3D geometry and motions of the heart. Deep learning image registration (DLIR) is a robust wa...
Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. However, the requirement of excessive high-quality ground-truth data hi...
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