Abstract
The value of pulmonary function test (PFT) data is increasing due to the advent of the Coronavirus Infectious Disease 19 (COVID-19) and increased respiratory disease. However, these PFT data cannot be directly used in clinical studies, because PFT results are stored in raw image files. In this study, the classification and itemization medical image (CIMI) system generates valuable data from raw PFT images by automatically classifying various PFT results, extracting texts, and storing them in the PFT database and Excel files. The deep-learning-based optical character recognition (OCR) technology was mainly used in CIMI to classify and itemize PFT images in St. Mary’s Hospital. CIMI classified seven types and itemized 913,059 texts from 14,720 PFT image sheets, which cannot be done by humans. The number, type, and location of texts that can be extracted by PFT type are all different, but CIMI solves this issue by classifying the PFT image sheets by type, allowing researchers to analyze the data. To demonstrate the superiority of CIMI, the validation results of CIMI were compared to the results of the other four algorithms. A total of 70 randomly selected sheets (ten sheets from each type) and 33,550 texts were used for the validation. The accuracy of CIMI was 95%, which was the highest accuracy among the other four algorithms.
Highlights
Respiratory disease is one of the leading causes of death worldwide [1,2] long before the advent of Coronavirus Infectious Disease 19 (COVID-19) [3], the main symptom of which is lung failure.According to a report by the World Health Organization (WHO), the top five major causes of lung related severe illness are chronic obstructive pulmonary disease (COPD), asthma, acute lower respiratory tract infections, tuberculosis (TB), and lung cancer [4]
This study proposed classification and itemization medical image (CIMI), a deep-learning-based medical image Artificial intelligence (AI) processing system that classifies and extracts text from medical images
CIMI classifies pulmonary function testing (PFT) results, and extracts medical images to text in a standardized medical data form for big data or AI researchers
Summary
According to a report by the World Health Organization (WHO), the top five major causes of lung related severe illness are chronic obstructive pulmonary disease (COPD), asthma, acute lower respiratory tract infections, tuberculosis (TB), and lung cancer [4]. According to their statistics, each year, 4 million people die prematurely from chronic respiratory disease [5], with infants and young children susceptible [6].
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