Machine Learning - GastroView project
WE FIND AND TAG ANOMALIES IN CAPSULE ENDOSCOPY IMAGES
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Due to Deep Learning algorithms implemented in GastroView, it is possible to shorten time of examination and analysis of image received from capsule endoscopy by maximum of 70%.

01
How it works

STEP 1

During capsule endoscopy a capsule size of a large pill containing two wide-angle cameras, is sliding down the digestive tract and automatically recording insides of internal organs. Images recorded by cameras after being magnified eight times allows to notice changes approximate to 0,1 cm.

STEP 2

During 8 hours cameras take about 100 000 pictures. They are encoded and wirelessly transmitted to data recorder that the patient wears during the examination. Received video is later analyzed by a doctor.

STEP 3

Usual time of analysis and evaluation of the results of capsule endoscopy depends on diagnosed disease as well as on experience of the doctor and takes many hours. GastroView software is going to reduce that time by maximum of 70% and due to that costs reduction by approximately 50%. Simultaneously, the accuracy of performed data analysis increases as well as the number of diagnosed anomalies.

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