OBJECTIVE: This study aims to investigate the impact of adaptive statistical iterative reconstruction-Veo (ASIR-V) and deep learning image reconstruction (DLIR) algorithms on the quantification of pericoronary adipose tissue (PCAT) and epicardial adi...
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND: Pathologic complete response (pCR) following neoadjuvant chemotherapy (NACT) is a critical prognostic marker for patients with breast cancer, potentially allowing surgery omission. However, noninvasive and accurate pCR diagnosis remains a...
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) a...
U-Net is a commonly used model for medical image segmentation. However, when applied to chest X-ray images that show pathologies, it often fails to include these critical pathological areas in the generated masks. To address this limitation, in our s...
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: Exploring the dependencies between multimodal brain networks and integrating node features to enhance brain disease diagnosis remains a significant challenge. Some work has examined only brain connectivity changes in patient...
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: Orthognathic surgery consultations are essential for helping patients understand how their facial appearance may change after surgery. However, current visualization methods are often inefficient and inaccurate due to limite...
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: This study introduces multiscale feature learning to develop more robust and resilient activity recognition algorithms, aimed at accurately tracking and quantifying rehabilitation exercises while minimizing performance dispa...
Journal of applied clinical medical physics
Apr 23, 2025
BACKGROUND: Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods rely on manually annotated data for network training.
Intensifying urban heat extremes require efficient mitigation strategies; therefore, we propose a methodological framework for optimizing the implementation of urban green and cool roofs to reduce heat stress while maximizing their cost-effectiveness...
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