> top > docs > PMC:7782580 > spans > 30730-31953 > annotations

PMC:7782580 / 30730-31953 JSONTXT

Annnotations TAB JSON ListView MergeView

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
217 209-212 Gene denotes Tag Gene:404663

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T16 480-496 Phenotype denotes highly sensitive http://purl.obolibrary.org/obo/HP_0041092

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T237 0-284 Sentence denotes Popular image annotation tools (e.g., Labelme46 and VOTT47) are used to annotate various images and support common formats, such as Joint Photographic Experts Group (JPG), Portable Network Graphics (PNG), and Tag Image File Format (TIFF); these formats are not used in the DICOM data.
T238 285-462 Sentence denotes Therefore, we developed an annotation platform that does not require much storage space or transformations and can be deployed on a private cloud for security and local sharing.
T239 463-612 Sentence denotes Our eyes are not highly sensitive to grayscale images in regions with high average brightness48, resulting in relatively low identification accuracy.
T240 613-752 Sentence denotes The proposed pseudo-color method increased the information content of the medical images and facilitated the identification of the details.
T241 753-852 Sentence denotes PCA has been widely used for feature extraction and dimensionality reduction in image processing49.
T242 853-917 Sentence denotes We used PCA to determine the feature space of the sub-data sets.
T243 918-1017 Sentence denotes Each image in a specified sub-data set was represented as a linear combination of the eigenvectors.
T244 1018-1135 Sentence denotes Since the eigenvectors describe the most informative regions in the medical images, they represent each sub-data set.
T245 1136-1223 Sentence denotes We visualized the top-five eigenvectors of each sub-data set using an intuitive method.