Abstract
In this paper, we propose new diagnostic assist systems of medical images using deep learning algorithms. Specifically, we aim to develop a diagnostic support system for the very early stage of chronic obstructive pulmonary disease (COPD) based on the CT images. It is said that COPD is a disease that develops due to long-term smoking, and it is said that there are a large number of latent onset reserve forces. By discovering this COPD in the very early period 0 and improving the living conditions, subsequent severity can be avoided in many cases, so a system that will help diagnosis by professional radiologists is needed. We show the some experimental results examined by the constructed system.
Highlights
Chronic Obstructive Pulmonary Disease (COPD) is a disease added to target diseases of “Health Japan 21” planned by the Ministry of Health, Labor and Welfare as one of new lifestyle-related diseases since 2013 [1]
We propose new diagnostic assist systems of medical images using deep learning algorithms
1) Using the CT image of the whole body as input, a set of lung CT images is extracted by the classification system based on deep learning
Summary
Chronic Obstructive Pulmonary Disease (COPD) is a disease added to target diseases of “Health Japan 21” planned by the Ministry of Health, Labor and Welfare as one of new lifestyle-related diseases since 2013 [1]. COPD, known as “tobacco disease”, is a pulmonary chronic inflammatory disease caused by long-term inhalation exposure of harmful substances, mainly tobacco smoke. According to the Ministry of Health, Labor and Welfare Ministry survey of medical institutions visited by medical institutions, only about 260 thousand of them are receiving treatment, and 95% of patients are considered untreated. In areas like Hokkaido where smoking rate is high, some countermeasures are necessary in particular
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