CAD Model for Biomedical Image Processing for Digital Assistance

  • Sharma, Hitesh Kumar; 
  • Choudhury, Tanupriya; 
  • Choudhary, Richa; 
  • Um, Jung Sup; 
  • Sharma, Aarav
Citations

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초록

Insufficiency of doctors produces a high challenge for Biomedical Engineering to develop efficient assistance tools or applications which can be used as a supporting system (e.g., CAD) for doctors to diagnose diseases using biomedical images like CT-Scan, X-ray, MRI etc. COVID-19 is a highly communicable and extremely dangerous disease. Almost 1.36 billion people in the word are affected by the coronavirus till date. Two million people have died. This deadly disease has affected more than 150 countries in the world and still thousands of people are getting exposed to this disease daily. So early detection of the disease is really important and critical to save a person’s life. Coronavirus can be significantly detected through chest X-rays. With the help of Deep Learning and Neural Network, detection of COVID can be done quickly and cheaply. So, we are making use of a CNN Model to quickly detect whether a person has COVID-19 or not by inputting the X-ray images. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

키워드

Chest X-ray; CNN; COVID-19; Deep learning
제목
CAD Model for Biomedical Image Processing for Digital Assistance
저자
Sharma, Hitesh Kumar; Choudhury, Tanupriya; Choudhary, Richa; Um, Jung Sup; Sharma, Aarav
DOI
10.1007/978-981-99-1946-8_9
발행일
2023
유형
Conference paper
저널명
Lecture Notes in Networks and Systems
권
682 LNNS
페이지
81 ~ 91