Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.
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Brac University
2021
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| Accès en ligne: | http://hdl.handle.net/10361/14465 |
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10361-144652022-01-26T10:15:43Z Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices Rahman, Md. Nafis Nakib Sadik, Saif Abdullah Biswas, Anindya Tazul, Ratul Bin Alam, Golam Rabiul Department of Computer Science and Engineering, Brac University Anemia Point of Care Image Processing Non-Invasive Python OpenCV TensorFlow Keras This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. Cataloged from PDF version of thesis. Includes bibliographical references (pages 47-49). A medical procedure is described as non-invasive if there is no necessity for incision into the skin. Invasive methods can often be risky because there is a high chance of infection. That is why the medical sector is constantly trying to shift its momentum into non-invasive methods. The traditional method of detecting Anemia is by testing blood samples taken from the patient’s body. Anemia is a medical condition when the human body suffers from a lack of RBC. RBC is the carrier of oxygen to the blood. If not checked regularly, this may lead to kidney failure or even premature births. The situation gets worse in the rural areas of developing nations, where medical equipment is often unavailable. This study proposes a non-invasive point of care solution using images captured from mobile phone videos. Image processing is a vastly used technique around the world. Mostly because it allows various algorithms to be applied and reduces the build-up of noise and deformation during image processing. Usually, an Anemic patient’s blood contains less hemoglobin. Anemic blood transmits more light compared to normal blood, so the severity of anemia can be measured by analyzing the color of blood. Using the flashlight, the capturing of blood color was made possible without drawing blood. Hence, this paper tried to analyze the sample using python image processing that will enable the chances of a low-cost point of care solution for the detection of Anemia. Md. Nafis Nakib Rahman Saif Abdullah Sadik Anindya Biswas Ratul Bin Tazul B. Computer Science 2021-06-02T08:56:11Z 2021-06-02T08:56:11Z 2020 2020-04 Thesis ID: 16101195 ID: 16101222 ID: 16101185 ID: 16101201 http://hdl.handle.net/10361/14465 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 49 Pages application/pdf Brac University |
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Brac University |
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Institutional Repository |
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en_US |
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Anemia Point of Care Image Processing Non-Invasive Python OpenCV TensorFlow Keras |
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Anemia Point of Care Image Processing Non-Invasive Python OpenCV TensorFlow Keras Rahman, Md. Nafis Nakib Sadik, Saif Abdullah Biswas, Anindya Tazul, Ratul Bin Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. |
| author2 |
Alam, Golam Rabiul |
| author_facet |
Alam, Golam Rabiul Rahman, Md. Nafis Nakib Sadik, Saif Abdullah Biswas, Anindya Tazul, Ratul Bin |
| format |
Thesis |
| author |
Rahman, Md. Nafis Nakib Sadik, Saif Abdullah Biswas, Anindya Tazul, Ratul Bin |
| author_sort |
Rahman, Md. Nafis Nakib |
| title |
Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| title_short |
Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| title_full |
Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| title_fullStr |
Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| title_full_unstemmed |
Point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| title_sort |
point of care detection of anemia in non-invasive manner by using image processing and convolutional neural network with mobile devices |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14465 |
| work_keys_str_mv |
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