In clinical practice, frozen section (FS) images can be utilized to obtain the immediate pathological results of the patients in operation due to their fast production speed. However, compared with the formalin-fixed and paraffin-embedded (FFPE) imag...
Histopathological image segmentation is a laborious and time-intensive task, often requiring analysis from experienced pathologists for accurate examinations. To reduce this burden, supervised machine-learning approaches have been adopted using large...
Neural networks : the official journal of the International Neural Network Society
Feb 3, 2025
Semi-supervised learning with a graph-based approach has become increasingly popular in machine learning, particularly when dealing with situations where labeling data is a costly process. Graph Convolution Networks (GCNs) have been widely employed i...
International journal of neural systems
Feb 3, 2025
Few-shot segmentation (FSS) aims to reduce the need for manual annotation, which is both expensive and time-consuming. While FSS enhances model generalization to new concepts with only limited test samples, it still relies on a substantial amount of ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 3, 2025
Human epidermal growth factor receptor 2 (HER2) is an important biomarker for prognosis and prediction of treatment response in breast cancer (BC). HER2 scoring is typically evaluated by pathologist microscopic observation on immunohistochemistry (IH...
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2025
Weakly supervised instance segmentation (WSIS) aims to identify individual instances from weakly supervised semantic segmentation precisely. Existing WSIS techniques primarily employ a unified, fixed threshold to identify all peaks in semantic maps. ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 1, 2025
The early diagnosis of retinal disorders is essential in preventing permanent or partial blindness. Identifying these conditions promptly guarantees early treatment and prevents blindness. However, the challenge lies in accurately diagnosing these co...
Monitoring the microparticle transfer process in wastewater treatment systems is crucial for improving treatment performance. Supervised deep learning methods show high performance to automatically detect particles, but they rely on vast amounts of l...
Multiplexed positron emission tomography (mPET) imaging allows simultaneous observation of physiological and pathological information from multiple tracers in a single PET scan. Although supervised deep learning has demonstrated superior performance ...
Despite significant progress in 3D medical image segmentation using deep learning, manual annotation remains a labor-intensive bottleneck. Self-supervised mask propagation (SMP) methods have emerged to alleviate this challenge, allowing intra-volume ...
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