Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application
Y Meng, Y Yang, M Hu, Z Zhang, X Zhou - Seminars in Cancer Biology, 2023 - Elsevier
Radiomics is the extraction of predefined mathematic features from medical images for
predicting variables of clinical interest. Recent research has demonstrated that radiomics …
predicting variables of clinical interest. Recent research has demonstrated that radiomics …
Revolutionizing digital pathology with the power of generative artificial intelligence and foundation models
Digital pathology has transformed the traditional pathology practice of analyzing tissue
under a microscope into a computer vision workflow. Whole slide imaging allows …
under a microscope into a computer vision workflow. Whole slide imaging allows …
Donet: Deep de-overlapping network for cytology instance segmentation
Cell instance segmentation in cytology images has significant importance for biology
analysis and cancer screening, while remains challenging due to 1) the extensive …
analysis and cancer screening, while remains challenging due to 1) the extensive …
[HTML][HTML] A systematic review of deep learning-based cervical cytology screening: from cell identification to whole slide image analysis
P Jiang, X Li, H Shen, Y Chen, L Wang, H Chen… - Artificial Intelligence …, 2023 - Springer
Cervical cancer is one of the most common cancers in daily life. Early detection and
diagnosis can effectively help facilitate subsequent clinical treatment and management. With …
diagnosis can effectively help facilitate subsequent clinical treatment and management. With …
Image quality-aware diagnosis via meta-knowledge co-embedding
Medical images usually suffer from image degradation in clinical practice, leading to
decreased performance of deep learning-based models. To resolve this problem, most …
decreased performance of deep learning-based models. To resolve this problem, most …
Multi-class nucleus detection and classification using deep convolutional neural network with enhanced high dimensional dissimilarity translation model on cervical …
Advanced cervical screening via liquid-based cytology (LBC)/Pap smear is a highly efficient
precancerous cell detection tool based on cell image analysis, in which cells are classified …
precancerous cell detection tool based on cell image analysis, in which cells are classified …
[HTML][HTML] Digital staining in optical microscopy using deep learning-a review
Until recently, conventional biochemical staining had the undisputed status as well-
established benchmark for most biomedical problems related to clinical diagnostics …
established benchmark for most biomedical problems related to clinical diagnostics …
[HTML][HTML] Towards artificial intelligence applications in next generation cytopathology
E Giarnieri, S Scardapane - Biomedicines, 2023 - mdpi.com
Over the last 20 years we have seen an increase in techniques in the field of computational
pathology and machine learning, improving our ability to analyze and interpret imaging …
pathology and machine learning, improving our ability to analyze and interpret imaging …
A CNN-based approach for joint segmentation and quantification of nuclei and NORs in AgNOR-stained images
Abstract Background and Objective Oral cancer is the sixth most common kind of human
cancer. Brush cytology for counting Argyrophilic Nucleolar Organizer Regions (AgNORs) …
cancer. Brush cytology for counting Argyrophilic Nucleolar Organizer Regions (AgNORs) …
[HTML][HTML] Morphology-based deep learning enables accurate detection of senescence in mesenchymal stem cell cultures
L He, M Li, X Wang, X Wu, G Yue, T Wang, Y Zhou… - BMC biology, 2024 - Springer
Background Cell senescence is a sign of aging and plays a significant role in the
pathogenesis of age-related disorders. For cell therapy, senescence may compromise the …
pathogenesis of age-related disorders. For cell therapy, senescence may compromise the …