Results 181 to 190 of about 496,156 (331)
Enhanced image annotations based on spatial information extraction and ontologies
Current research on image annotation often represents images in terms of labelled regions or objects, but pays little attention to the spatial positions or relationships between those regions or objects.
Lewis, Paul H.+3 more
core
POCS-Based Annotation Method Using Kernel PCA for Semantic Image Retrieval [PDF]
Takahiro Ogawa, Miki Haseyama
openalex +1 more source
Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane+16 more
wiley +1 more source
Clustering based multi-label classification for image annotation and retrieval [PDF]
Gulisong Nasierding+2 more
openalex +1 more source
Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer
We used whole exome and RNA‐sequencing to profile divergent genomic and transcriptomic landscapes of microsatellite stable (MSS) and microsatellite instable (MSI) colorectal cancer. Alterations were classified using a computational score for integrative cancer variant annotation and prioritization.
Efstathios‐Iason Vlachavas+15 more
wiley +1 more source
Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien+7 more
wiley +1 more source
An Adaptive Low-Rank Modeling-Based Active Learning Method for Medical Image Annotation. [PDF]
He S+7 more
europepmc +1 more source
How to select slices for annotation to train best-performing deep learning segmentation models for cross-sectional medical images? [PDF]
Automated segmentation of medical images heavily relies on the availability of precise manual annotations. However, generating these annotations is often time-consuming, expensive, and sometimes requires specialized expertise (especially for cross-sectional medical images).
arxiv
The study evaluated the function and therapeutic implications of PRAME in basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). The findings demonstrate that PRAME impairs keratinocyte differentiation pathways. Furthermore, PRAME impairs anticancer response to retinoid compounds in BCC and SCC cells.
Brandon Ramchatesingh+6 more
wiley +1 more source
Evaluation of web-based annotation of ophthalmic images for multicentric clinical trials
GauravY Shah+3 more
openalex +1 more source