histomicstk

This histomicstk package contains algorithms for fundamental image analysis tasks including color normalization, color deconvolution, filtering to enhance commonly found objects/structures, cell/nuclei segmentation, feature extraction, and tissue detection. It also contains algorithms and workflows to parse annotations polygons into masks for training and validating algorithms and vice versa.

• utils
  • compute_tile_foreground_fraction()
  • convert_image_to_matrix()
  • convert_matrix_to_image()
  • del2()
  • eigen()
  • exclude_nonfinite()
  • fit_poisson_mixture()
  • gradient_diffusion()
  • hessian()
  • merge_colinear()
  • sample_pixels()
  • simple_mask()
• preprocessing
  • color space conversion
  • color deconvolution
  • color normalization
  • data augmentation
• filters
  • edge/gradient filters
  • shape filters
• segmentation
  • embed_boundaries()
  • rag()
  • rag_add_layer()
  • rag_color()
  • simple_mask()
  • label mask processing
  • level-set segmentation
  • nuclei segmentation
  • positive pixel counting
• features
  • compute_fsd_features()
  • compute_global_cell_graph_features()
  • compute_gradient_features()
  • compute_haralick_features()
  • compute_intensity_features()
  • compute_morphometry_features()
  • compute_nuclei_features()
  • graycomatrixext()
• annotations and masks
  • Annotation database backup and sqlite parser
  • Mosaic review gallery
  • Annotations to semantic segmentation masks
  • Annotations to object segmentation masks
  • Masks to annotations
  • Annotation and mask utilities
  • Polygon merger
• saliency (tissue/cellularity detection)
  • Tissue detection
  • Cellularity detection (using thresholding)
  • Cellularity detection (using superpixels)
• workflows
  • Workflow runner
  • Specific workflows