TBChestXRay / Git / Diff of /README.md

Datasets:

GeorgeSullivan/

TBChestXRay

Downloads: 1

Data:

De-identified

Image Specialty:

Infectious Diseases

Radiology

Respiratory Medicine Medical Imaging Technique:

X-Ray Medical Imaging Region:

Chest

Lungs Clinical Purpose:

Diagnosis

Screening Task:

Classification

Detection License:

Other

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<div class="sc-kdrUpr eZtUed"><div class="sc-UEtKG dGqiYy sc-hDzlxo bEIZRR"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"></div></div></div><div class="sc-fHzVOS cUYeeo"><div class="sc-davvxH flNyFK"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-jCNfQM igJSrG"><p><strong><em><em></em></em></strong><strong><em><strong>Tuberculosis (TB) Chest X-ray Database</strong></em></strong><strong><em></em></strong><br>
A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 700 TB images publicly accessible and 2800 TB images can be downloaded from NIAID TB portal[3] by signing an agreement, and 3500 normal images. </p>
<p>Note: -The research team managed to classify TB and Normal Chest X-ray images with an accuracy of 98.3%. This scholarly work is published in IEEE Access. Please make sure you give credit to us while using the dataset, code, and trained models.</p>
<p><strong>Credit should go to the following:</strong><br>
Tawsifur Rahman, Amith Khandakar, Muhammad A. Kadir, Khandaker R. Islam, Khandaker F. Islam, Zaid B. Mahbub,  Mohamed Arselene Ayari, Muhammad E. H. Chowdhury. (2020)  "Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization".  IEEE Access, Vol. 8, pp 191586 - 191601. DOI. 10.1109/ACCESS.2020.3031384. <a rel="noreferrer nofollow" aria-label="Paper Link (opens in a new tab)" target="_blank" href="https://ieeexplore.ieee.org/document/9224622">Paper Link</a></p>
<p>To view images please check image folders and references of each image are provided in the metadata.csv.</p>
...
<p><strong>References:</strong><br>
[1]    S. Jaeger, S. Candemir, S. Antani, Y.-X. J. Wáng, P.-X. Lu, and G. Thoma, "Two public chest X-ray datasets for computer-aided screening of pulmonary diseases," Quantitative imaging in medicine and surgery, vol. 4 (6), p. 475(2014)<br>
[2]    B. P. Health. (2020). BELARUS TUBERCULOSIS PORTAL  [Online]. Available: <a rel="noreferrer nofollow" aria-label="http://tuberculosis.by/ (opens in a new tab)" target="_blank" href="http://tuberculosis.by/">http://tuberculosis.by/</a>. [Accessed on 09-June-2020]<br>
[3]    NIAID TB portal program dataset [Online]. Available: <a rel="noreferrer nofollow" aria-label="https://tbportals.niaid.nih.gov/download-data (opens in a new tab)" target="_blank" href="https://tbportals.niaid.nih.gov/download-data">https://tbportals.niaid.nih.gov/download-data</a>.<br>
[4]    kaggle. RSNA Pneumonia Detection Challenge  [Online]. Available: <a aria-label="https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data (opens in a new tab)" target="_blank" href="https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data">https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data</a>. [Accessed on 09-June-2020]</p></div></div></div>

	a/README.md		b/README.md
1	<div class="sc-kdrUpr eZtUed"><div class="sc-UEtKG dGqiYy sc-hDzlxo bEIZRR"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-fHzVOS cUYeeo"><div class="sc-davvxH flNyFK"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-jCNfQM igJSrG"><p><strong><em><em></em></em></strong><strong><em><strong>Tuberculosis (TB) Chest X-ray Database</strong></em></strong><strong><em></em></strong><br>	1	<div class="sc-kdrUpr eZtUed"><div class="sc-UEtKG dGqiYy sc-hDzlxo bEIZRR"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"></div></div></div><div class="sc-fHzVOS cUYeeo"><div class="sc-davvxH flNyFK"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-jCNfQM igJSrG"><p><strong><em><em></em></em></strong><strong><em><strong>Tuberculosis (TB) Chest X-ray Database</strong></em></strong><strong><em></em></strong><br>
2	A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 700 TB images publicly accessible and 2800 TB images can be downloaded from NIAID TB portal[3] by signing an agreement, and 3500 normal images. </p>	2	A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 700 TB images publicly accessible and 2800 TB images can be downloaded from NIAID TB portal[3] by signing an agreement, and 3500 normal images. </p>
3	<p>Note: -The research team managed to classify TB and Normal Chest X-ray images with an accuracy of 98.3%. This scholarly work is published in IEEE Access. Please make sure you give credit to us while using the dataset, code, and trained models.</p>	3	<p>Note: -The research team managed to classify TB and Normal Chest X-ray images with an accuracy of 98.3%. This scholarly work is published in IEEE Access. Please make sure you give credit to us while using the dataset, code, and trained models.</p>
4	<p><strong>Credit should go to the following:</strong><br>	4	<p><strong>Credit should go to the following:</strong><br>
5	Tawsifur Rahman, Amith Khandakar, Muhammad A. Kadir, Khandaker R. Islam, Khandaker F. Islam, Zaid B. Mahbub, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury. (2020) "Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization". IEEE Access, Vol. 8, pp 191586 - 191601. DOI. 10.1109/ACCESS.2020.3031384. <a rel="noreferrer nofollow" aria-label="Paper Link (opens in a new tab)" target="_blank" href="https://ieeexplore.ieee.org/document/9224622">Paper Link</a></p>	5	Tawsifur Rahman, Amith Khandakar, Muhammad A. Kadir, Khandaker R. Islam, Khandaker F. Islam, Zaid B. Mahbub, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury. (2020) "Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization". IEEE Access, Vol. 8, pp 191586 - 191601. DOI. 10.1109/ACCESS.2020.3031384. <a rel="noreferrer nofollow" aria-label="Paper Link (opens in a new tab)" target="_blank" href="https://ieeexplore.ieee.org/document/9224622">Paper Link</a></p>
6	<p>To view images please check image folders and references of each image are provided in the metadata.csv.</p>	6	<p>To view images please check image folders and references of each image are provided in the metadata.csv.</p>
	...		...
43	<p><strong>References:</strong><br>	43	<p><strong>References:</strong><br>
44	[1] S. Jaeger, S. Candemir, S. Antani, Y.-X. J. Wáng, P.-X. Lu, and G. Thoma, "Two public chest X-ray datasets for computer-aided screening of pulmonary diseases," Quantitative imaging in medicine and surgery, vol. 4 (6), p. 475(2014)<br>	44	[1] S. Jaeger, S. Candemir, S. Antani, Y.-X. J. Wáng, P.-X. Lu, and G. Thoma, "Two public chest X-ray datasets for computer-aided screening of pulmonary diseases," Quantitative imaging in medicine and surgery, vol. 4 (6), p. 475(2014)<br>
45	[2] B. P. Health. (2020). BELARUS TUBERCULOSIS PORTAL [Online]. Available: <a rel="noreferrer nofollow" aria-label="http://tuberculosis.by/ (opens in a new tab)" target="_blank" href="http://tuberculosis.by/">http://tuberculosis.by/</a>. [Accessed on 09-June-2020]<br>	45	[2] B. P. Health. (2020). BELARUS TUBERCULOSIS PORTAL [Online]. Available: <a rel="noreferrer nofollow" aria-label="http://tuberculosis.by/ (opens in a new tab)" target="_blank" href="http://tuberculosis.by/">http://tuberculosis.by/</a>. [Accessed on 09-June-2020]<br>
46	[3] NIAID TB portal program dataset [Online]. Available: <a rel="noreferrer nofollow" aria-label="https://tbportals.niaid.nih.gov/download-data (opens in a new tab)" target="_blank" href="https://tbportals.niaid.nih.gov/download-data">https://tbportals.niaid.nih.gov/download-data</a>.<br>	46	[3] NIAID TB portal program dataset [Online]. Available: <a rel="noreferrer nofollow" aria-label="https://tbportals.niaid.nih.gov/download-data (opens in a new tab)" target="_blank" href="https://tbportals.niaid.nih.gov/download-data">https://tbportals.niaid.nih.gov/download-data</a>.<br>
47	[4] kaggle. RSNA Pneumonia Detection Challenge [Online]. Available: <a aria-label="https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data (opens in a new tab)" target="_blank" href="https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data">https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data</a>. [Accessed on 09-June-2020]</p></div></div></div>	47	[4] kaggle. RSNA Pneumonia Detection Challenge [Online]. Available: <a aria-label="https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data (opens in a new tab)" target="_blank" href="https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data">https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/data</a>. [Accessed on 09-June-2020]</p></div></div></div>