{'fraction_non_alphanumeric': 0.013647642679900745, 'fraction_numerical': 0.0, 'mean_word_length': 5.560975609756097, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Image-assisted analysis of pathologist slide review as a means of informing optimal digital slide acquisition strategies

In digital pathology, the practice of scanning slides at a single resolution results in more data than is clinically useful. In contrast, using a light microscope, the pathologist adapts magnification according to specimen content. We developed a method of digitizing the analog microscope workflows of pathologists using a microscope camera and video mosaicking with the Scale Invariant Feature Transform (SIFT). Matching this digital record to the whole slide image generates a slide interaction map over time and magnification tiers. The results of the pilot studies suggest data size can be significantly reduced without diminishing the information content required for diagnosis.