In recent years, online customer reviews and social media platforms have significantly impacted individuals' daily lives. Despite the generally short nature of textual content on these platforms, they convey a wide range of user sentiments. However, ...
BACKGROUND: Understanding how sensory stimuli are represented across different brains, species, and artificial neural networks is a critical topic in neuroscience. Traditional methods for comparing these representations typically rely on supervised a...
BACKGROUND: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment abnormal regions, such as cerebral edema and hemorrhages, using only healthy training data. Recent advancements in generative models have achieved suc...
Neural networks : the official journal of the International Neural Network Society
Apr 5, 2025
Current unsupervised reinforcement learning methods often overlook reward nonstationarity during pre-training and the forgetting of exploratory behavior during fine-tuning. Our study introduces Self-Reference (SR), a novel add-on module designed to a...
Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and computed tomography angiography (CTA) is essential in providing supportive information for diagnosing and treatment planning of multiple intracranial vascul...
IEEE journal of biomedical and health informatics
Apr 4, 2025
It is difficult for general registration methods to establish the fine correspondence between images with complex anatomical structures. To overcome the above problem, this work presents SFM-Net, an unsupervised multi-stage semantic feature-based net...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Deformable image registration, as a fundamental prerequisite for many medical image analysis tasks, has received considerable attention. However, existing methods suffer from two key issues: 1) single-stream methods that stack moving and fixed images...
Unsupervised domain adaptation (UDA) in medical image segmentation aims to improve the generalization of deep models by alleviating domain gaps caused by inconsistency across equipment, imaging protocols, and patient conditions. However, existing UDA...
The microbial rare biosphere, composed of low-abundance microorganisms in a community, lacks a standardized delineation method for its definition. Currently, most studies rely on arbitrary thresholds to define the microbial rare biosphere (e.g., 0.1%...
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